No version for distro humble showing jade. Known supported distros are highlighted in the buttons above.
Package symbol

libhaloc package from libhaloc repo

libhaloc

ROS Distro
jade

Package Summary

Tags No category tags.
Version 0.0.1
License BSD
Build type CATKIN
Use RECOMMENDED

Repository Summary

Checkout URI https://github.com/srv/libhaloc.git
VCS Type git
VCS Version indigo
Last Updated 2016-01-21
Dev Status MAINTAINED
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Package Description

Hash-Based Loop Closing

Additional Links

Maintainers

  • Pep Lluis Negre

Authors

  • Pep Lluis Negre

libhaloc

ROS library for HAsh-based LOop Closure detection. This library provides the tools for loop closing detection based on image hashing. Image hashing consists of representing every image with a small vector (hash). Then the hash of image A can be compared with the hash of image B in a super fast way in order to determine if images are similar.

The image hashing implemented in this library is based on SIFT features so, since SIFT is invariant to scale and rotation, the image hashing will be also invariant to these properties.

The library works for both mono and stereo cameras and provides a transformation (2d for mono and 3d for stereo) when loop closures are found.

[Autonomous Robots][paper]

CITATION:

@Article{Negre Carrasco2015,
   author="Negre Carrasco, Pep Lluis
   and Bonin-Font, Francisco
   and Oliver-Codina, Gabriel",
   title="Global image signature for visual loop-closure detection",
   journal="Autonomous Robots",
   year="2015",
   pages="1--15",
   issn="1573-7527",
   doi="10.1007/s10514-015-9522-4",
   url="http://dx.doi.org/10.1007/s10514-015-9522-4"
}

How to prepare your SLAM node

Modify your CMakeLists.txt as follows:

# Add this line before catkin_package()
find_package(libhaloc REQUIRED)

# Include the libhaloc directories
include_directories(
  ${catkin_INCLUDE_DIRS}
  ${libhaloc_INCLUDE_DIRS}
  ...
  )

# Link your executable with libhaloc
target_link_libraries(your_executable_here
  ${catkin_LIBRARIES}
  ${libhaloc_LIBRARIES}
  ...
  )

Include the header in your .cpp file:

#include <libhaloc/lc.h>

How to call the library

You can use libhaloc in two different ways:

  • To generate the image hashes and then, use your own techniques to compare this hashes and retrieve the best candidates to close loop.
  • To use the full power of libhaloc to search loop closing candidates and compute the homogeneous transformation (if any).

To use libhaloc as the first option:

  • Declare your haloc object:
haloc::Hash haloc_;

  • Init your haloc object (only once):
if (!hash_.isInitialized())
   hash_.init(c_cluster_.getSift());

  • Then, for every new image you process, extract its descriptor matrix (SIFT)
cv::Mat sift;
// Use opencv to extract the SIFT matrix and then:
vector<float> current_hash = hash_.getHash(sift);

  • Now, you can store all the hashes into a table and compare it:
std::vector<float> matches;
for (uint i=0; i<my_table.size(); i++)
{
   float m = hash_.match(current_hash, my_table[i]);
   matches.push_back(matches);
}

  • Finally, sort the vector of matches from smallest to largest. Take the first 1, 2, 3 or 4 smallest values as candidates to close loop.

To use libhaloc as the second option:

File truncated at 100 lines see the full file

CHANGELOG
No CHANGELOG found.

Wiki Tutorials

This package does not provide any links to tutorials in it's rosindex metadata. You can check on the ROS Wiki Tutorials page for the package.

Package Dependencies

System Dependencies

No direct system dependencies.

Dependant Packages

Name Deps
stereo_slam

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged libhaloc at Robotics Stack Exchange

No version for distro jazzy showing jade. Known supported distros are highlighted in the buttons above.
Package symbol

libhaloc package from libhaloc repo

libhaloc

ROS Distro
jade

Package Summary

Tags No category tags.
Version 0.0.1
License BSD
Build type CATKIN
Use RECOMMENDED

Repository Summary

Checkout URI https://github.com/srv/libhaloc.git
VCS Type git
VCS Version indigo
Last Updated 2016-01-21
Dev Status MAINTAINED
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Package Description

Hash-Based Loop Closing

Additional Links

Maintainers

  • Pep Lluis Negre

Authors

  • Pep Lluis Negre

libhaloc

ROS library for HAsh-based LOop Closure detection. This library provides the tools for loop closing detection based on image hashing. Image hashing consists of representing every image with a small vector (hash). Then the hash of image A can be compared with the hash of image B in a super fast way in order to determine if images are similar.

The image hashing implemented in this library is based on SIFT features so, since SIFT is invariant to scale and rotation, the image hashing will be also invariant to these properties.

The library works for both mono and stereo cameras and provides a transformation (2d for mono and 3d for stereo) when loop closures are found.

[Autonomous Robots][paper]

CITATION:

@Article{Negre Carrasco2015,
   author="Negre Carrasco, Pep Lluis
   and Bonin-Font, Francisco
   and Oliver-Codina, Gabriel",
   title="Global image signature for visual loop-closure detection",
   journal="Autonomous Robots",
   year="2015",
   pages="1--15",
   issn="1573-7527",
   doi="10.1007/s10514-015-9522-4",
   url="http://dx.doi.org/10.1007/s10514-015-9522-4"
}

How to prepare your SLAM node

Modify your CMakeLists.txt as follows:

# Add this line before catkin_package()
find_package(libhaloc REQUIRED)

# Include the libhaloc directories
include_directories(
  ${catkin_INCLUDE_DIRS}
  ${libhaloc_INCLUDE_DIRS}
  ...
  )

# Link your executable with libhaloc
target_link_libraries(your_executable_here
  ${catkin_LIBRARIES}
  ${libhaloc_LIBRARIES}
  ...
  )

Include the header in your .cpp file:

#include <libhaloc/lc.h>

How to call the library

You can use libhaloc in two different ways:

  • To generate the image hashes and then, use your own techniques to compare this hashes and retrieve the best candidates to close loop.
  • To use the full power of libhaloc to search loop closing candidates and compute the homogeneous transformation (if any).

To use libhaloc as the first option:

  • Declare your haloc object:
haloc::Hash haloc_;

  • Init your haloc object (only once):
if (!hash_.isInitialized())
   hash_.init(c_cluster_.getSift());

  • Then, for every new image you process, extract its descriptor matrix (SIFT)
cv::Mat sift;
// Use opencv to extract the SIFT matrix and then:
vector<float> current_hash = hash_.getHash(sift);

  • Now, you can store all the hashes into a table and compare it:
std::vector<float> matches;
for (uint i=0; i<my_table.size(); i++)
{
   float m = hash_.match(current_hash, my_table[i]);
   matches.push_back(matches);
}

  • Finally, sort the vector of matches from smallest to largest. Take the first 1, 2, 3 or 4 smallest values as candidates to close loop.

To use libhaloc as the second option:

File truncated at 100 lines see the full file

CHANGELOG
No CHANGELOG found.

Wiki Tutorials

This package does not provide any links to tutorials in it's rosindex metadata. You can check on the ROS Wiki Tutorials page for the package.

Package Dependencies

System Dependencies

No direct system dependencies.

Dependant Packages

Name Deps
stereo_slam

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged libhaloc at Robotics Stack Exchange

No version for distro kilted showing jade. Known supported distros are highlighted in the buttons above.
Package symbol

libhaloc package from libhaloc repo

libhaloc

ROS Distro
jade

Package Summary

Tags No category tags.
Version 0.0.1
License BSD
Build type CATKIN
Use RECOMMENDED

Repository Summary

Checkout URI https://github.com/srv/libhaloc.git
VCS Type git
VCS Version indigo
Last Updated 2016-01-21
Dev Status MAINTAINED
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Package Description

Hash-Based Loop Closing

Additional Links

Maintainers

  • Pep Lluis Negre

Authors

  • Pep Lluis Negre

libhaloc

ROS library for HAsh-based LOop Closure detection. This library provides the tools for loop closing detection based on image hashing. Image hashing consists of representing every image with a small vector (hash). Then the hash of image A can be compared with the hash of image B in a super fast way in order to determine if images are similar.

The image hashing implemented in this library is based on SIFT features so, since SIFT is invariant to scale and rotation, the image hashing will be also invariant to these properties.

The library works for both mono and stereo cameras and provides a transformation (2d for mono and 3d for stereo) when loop closures are found.

[Autonomous Robots][paper]

CITATION:

@Article{Negre Carrasco2015,
   author="Negre Carrasco, Pep Lluis
   and Bonin-Font, Francisco
   and Oliver-Codina, Gabriel",
   title="Global image signature for visual loop-closure detection",
   journal="Autonomous Robots",
   year="2015",
   pages="1--15",
   issn="1573-7527",
   doi="10.1007/s10514-015-9522-4",
   url="http://dx.doi.org/10.1007/s10514-015-9522-4"
}

How to prepare your SLAM node

Modify your CMakeLists.txt as follows:

# Add this line before catkin_package()
find_package(libhaloc REQUIRED)

# Include the libhaloc directories
include_directories(
  ${catkin_INCLUDE_DIRS}
  ${libhaloc_INCLUDE_DIRS}
  ...
  )

# Link your executable with libhaloc
target_link_libraries(your_executable_here
  ${catkin_LIBRARIES}
  ${libhaloc_LIBRARIES}
  ...
  )

Include the header in your .cpp file:

#include <libhaloc/lc.h>

How to call the library

You can use libhaloc in two different ways:

  • To generate the image hashes and then, use your own techniques to compare this hashes and retrieve the best candidates to close loop.
  • To use the full power of libhaloc to search loop closing candidates and compute the homogeneous transformation (if any).

To use libhaloc as the first option:

  • Declare your haloc object:
haloc::Hash haloc_;

  • Init your haloc object (only once):
if (!hash_.isInitialized())
   hash_.init(c_cluster_.getSift());

  • Then, for every new image you process, extract its descriptor matrix (SIFT)
cv::Mat sift;
// Use opencv to extract the SIFT matrix and then:
vector<float> current_hash = hash_.getHash(sift);

  • Now, you can store all the hashes into a table and compare it:
std::vector<float> matches;
for (uint i=0; i<my_table.size(); i++)
{
   float m = hash_.match(current_hash, my_table[i]);
   matches.push_back(matches);
}

  • Finally, sort the vector of matches from smallest to largest. Take the first 1, 2, 3 or 4 smallest values as candidates to close loop.

To use libhaloc as the second option:

File truncated at 100 lines see the full file

CHANGELOG
No CHANGELOG found.

Wiki Tutorials

This package does not provide any links to tutorials in it's rosindex metadata. You can check on the ROS Wiki Tutorials page for the package.

Package Dependencies

System Dependencies

No direct system dependencies.

Dependant Packages

Name Deps
stereo_slam

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged libhaloc at Robotics Stack Exchange

No version for distro rolling showing jade. Known supported distros are highlighted in the buttons above.
Package symbol

libhaloc package from libhaloc repo

libhaloc

ROS Distro
jade

Package Summary

Tags No category tags.
Version 0.0.1
License BSD
Build type CATKIN
Use RECOMMENDED

Repository Summary

Checkout URI https://github.com/srv/libhaloc.git
VCS Type git
VCS Version indigo
Last Updated 2016-01-21
Dev Status MAINTAINED
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Package Description

Hash-Based Loop Closing

Additional Links

Maintainers

  • Pep Lluis Negre

Authors

  • Pep Lluis Negre

libhaloc

ROS library for HAsh-based LOop Closure detection. This library provides the tools for loop closing detection based on image hashing. Image hashing consists of representing every image with a small vector (hash). Then the hash of image A can be compared with the hash of image B in a super fast way in order to determine if images are similar.

The image hashing implemented in this library is based on SIFT features so, since SIFT is invariant to scale and rotation, the image hashing will be also invariant to these properties.

The library works for both mono and stereo cameras and provides a transformation (2d for mono and 3d for stereo) when loop closures are found.

[Autonomous Robots][paper]

CITATION:

@Article{Negre Carrasco2015,
   author="Negre Carrasco, Pep Lluis
   and Bonin-Font, Francisco
   and Oliver-Codina, Gabriel",
   title="Global image signature for visual loop-closure detection",
   journal="Autonomous Robots",
   year="2015",
   pages="1--15",
   issn="1573-7527",
   doi="10.1007/s10514-015-9522-4",
   url="http://dx.doi.org/10.1007/s10514-015-9522-4"
}

How to prepare your SLAM node

Modify your CMakeLists.txt as follows:

# Add this line before catkin_package()
find_package(libhaloc REQUIRED)

# Include the libhaloc directories
include_directories(
  ${catkin_INCLUDE_DIRS}
  ${libhaloc_INCLUDE_DIRS}
  ...
  )

# Link your executable with libhaloc
target_link_libraries(your_executable_here
  ${catkin_LIBRARIES}
  ${libhaloc_LIBRARIES}
  ...
  )

Include the header in your .cpp file:

#include <libhaloc/lc.h>

How to call the library

You can use libhaloc in two different ways:

  • To generate the image hashes and then, use your own techniques to compare this hashes and retrieve the best candidates to close loop.
  • To use the full power of libhaloc to search loop closing candidates and compute the homogeneous transformation (if any).

To use libhaloc as the first option:

  • Declare your haloc object:
haloc::Hash haloc_;

  • Init your haloc object (only once):
if (!hash_.isInitialized())
   hash_.init(c_cluster_.getSift());

  • Then, for every new image you process, extract its descriptor matrix (SIFT)
cv::Mat sift;
// Use opencv to extract the SIFT matrix and then:
vector<float> current_hash = hash_.getHash(sift);

  • Now, you can store all the hashes into a table and compare it:
std::vector<float> matches;
for (uint i=0; i<my_table.size(); i++)
{
   float m = hash_.match(current_hash, my_table[i]);
   matches.push_back(matches);
}

  • Finally, sort the vector of matches from smallest to largest. Take the first 1, 2, 3 or 4 smallest values as candidates to close loop.

To use libhaloc as the second option:

File truncated at 100 lines see the full file

CHANGELOG
No CHANGELOG found.

Wiki Tutorials

This package does not provide any links to tutorials in it's rosindex metadata. You can check on the ROS Wiki Tutorials page for the package.

Package Dependencies

System Dependencies

No direct system dependencies.

Dependant Packages

Name Deps
stereo_slam

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged libhaloc at Robotics Stack Exchange

No version for distro ardent showing jade. Known supported distros are highlighted in the buttons above.
Package symbol

libhaloc package from libhaloc repo

libhaloc

ROS Distro
jade

Package Summary

Tags No category tags.
Version 0.0.1
License BSD
Build type CATKIN
Use RECOMMENDED

Repository Summary

Checkout URI https://github.com/srv/libhaloc.git
VCS Type git
VCS Version indigo
Last Updated 2016-01-21
Dev Status MAINTAINED
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Package Description

Hash-Based Loop Closing

Additional Links

Maintainers

  • Pep Lluis Negre

Authors

  • Pep Lluis Negre

libhaloc

ROS library for HAsh-based LOop Closure detection. This library provides the tools for loop closing detection based on image hashing. Image hashing consists of representing every image with a small vector (hash). Then the hash of image A can be compared with the hash of image B in a super fast way in order to determine if images are similar.

The image hashing implemented in this library is based on SIFT features so, since SIFT is invariant to scale and rotation, the image hashing will be also invariant to these properties.

The library works for both mono and stereo cameras and provides a transformation (2d for mono and 3d for stereo) when loop closures are found.

[Autonomous Robots][paper]

CITATION:

@Article{Negre Carrasco2015,
   author="Negre Carrasco, Pep Lluis
   and Bonin-Font, Francisco
   and Oliver-Codina, Gabriel",
   title="Global image signature for visual loop-closure detection",
   journal="Autonomous Robots",
   year="2015",
   pages="1--15",
   issn="1573-7527",
   doi="10.1007/s10514-015-9522-4",
   url="http://dx.doi.org/10.1007/s10514-015-9522-4"
}

How to prepare your SLAM node

Modify your CMakeLists.txt as follows:

# Add this line before catkin_package()
find_package(libhaloc REQUIRED)

# Include the libhaloc directories
include_directories(
  ${catkin_INCLUDE_DIRS}
  ${libhaloc_INCLUDE_DIRS}
  ...
  )

# Link your executable with libhaloc
target_link_libraries(your_executable_here
  ${catkin_LIBRARIES}
  ${libhaloc_LIBRARIES}
  ...
  )

Include the header in your .cpp file:

#include <libhaloc/lc.h>

How to call the library

You can use libhaloc in two different ways:

  • To generate the image hashes and then, use your own techniques to compare this hashes and retrieve the best candidates to close loop.
  • To use the full power of libhaloc to search loop closing candidates and compute the homogeneous transformation (if any).

To use libhaloc as the first option:

  • Declare your haloc object:
haloc::Hash haloc_;

  • Init your haloc object (only once):
if (!hash_.isInitialized())
   hash_.init(c_cluster_.getSift());

  • Then, for every new image you process, extract its descriptor matrix (SIFT)
cv::Mat sift;
// Use opencv to extract the SIFT matrix and then:
vector<float> current_hash = hash_.getHash(sift);

  • Now, you can store all the hashes into a table and compare it:
std::vector<float> matches;
for (uint i=0; i<my_table.size(); i++)
{
   float m = hash_.match(current_hash, my_table[i]);
   matches.push_back(matches);
}

  • Finally, sort the vector of matches from smallest to largest. Take the first 1, 2, 3 or 4 smallest values as candidates to close loop.

To use libhaloc as the second option:

File truncated at 100 lines see the full file

CHANGELOG
No CHANGELOG found.

Wiki Tutorials

This package does not provide any links to tutorials in it's rosindex metadata. You can check on the ROS Wiki Tutorials page for the package.

Package Dependencies

System Dependencies

No direct system dependencies.

Dependant Packages

Name Deps
stereo_slam

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged libhaloc at Robotics Stack Exchange

No version for distro bouncy showing jade. Known supported distros are highlighted in the buttons above.
Package symbol

libhaloc package from libhaloc repo

libhaloc

ROS Distro
jade

Package Summary

Tags No category tags.
Version 0.0.1
License BSD
Build type CATKIN
Use RECOMMENDED

Repository Summary

Checkout URI https://github.com/srv/libhaloc.git
VCS Type git
VCS Version indigo
Last Updated 2016-01-21
Dev Status MAINTAINED
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Package Description

Hash-Based Loop Closing

Additional Links

Maintainers

  • Pep Lluis Negre

Authors

  • Pep Lluis Negre

libhaloc

ROS library for HAsh-based LOop Closure detection. This library provides the tools for loop closing detection based on image hashing. Image hashing consists of representing every image with a small vector (hash). Then the hash of image A can be compared with the hash of image B in a super fast way in order to determine if images are similar.

The image hashing implemented in this library is based on SIFT features so, since SIFT is invariant to scale and rotation, the image hashing will be also invariant to these properties.

The library works for both mono and stereo cameras and provides a transformation (2d for mono and 3d for stereo) when loop closures are found.

[Autonomous Robots][paper]

CITATION:

@Article{Negre Carrasco2015,
   author="Negre Carrasco, Pep Lluis
   and Bonin-Font, Francisco
   and Oliver-Codina, Gabriel",
   title="Global image signature for visual loop-closure detection",
   journal="Autonomous Robots",
   year="2015",
   pages="1--15",
   issn="1573-7527",
   doi="10.1007/s10514-015-9522-4",
   url="http://dx.doi.org/10.1007/s10514-015-9522-4"
}

How to prepare your SLAM node

Modify your CMakeLists.txt as follows:

# Add this line before catkin_package()
find_package(libhaloc REQUIRED)

# Include the libhaloc directories
include_directories(
  ${catkin_INCLUDE_DIRS}
  ${libhaloc_INCLUDE_DIRS}
  ...
  )

# Link your executable with libhaloc
target_link_libraries(your_executable_here
  ${catkin_LIBRARIES}
  ${libhaloc_LIBRARIES}
  ...
  )

Include the header in your .cpp file:

#include <libhaloc/lc.h>

How to call the library

You can use libhaloc in two different ways:

  • To generate the image hashes and then, use your own techniques to compare this hashes and retrieve the best candidates to close loop.
  • To use the full power of libhaloc to search loop closing candidates and compute the homogeneous transformation (if any).

To use libhaloc as the first option:

  • Declare your haloc object:
haloc::Hash haloc_;

  • Init your haloc object (only once):
if (!hash_.isInitialized())
   hash_.init(c_cluster_.getSift());

  • Then, for every new image you process, extract its descriptor matrix (SIFT)
cv::Mat sift;
// Use opencv to extract the SIFT matrix and then:
vector<float> current_hash = hash_.getHash(sift);

  • Now, you can store all the hashes into a table and compare it:
std::vector<float> matches;
for (uint i=0; i<my_table.size(); i++)
{
   float m = hash_.match(current_hash, my_table[i]);
   matches.push_back(matches);
}

  • Finally, sort the vector of matches from smallest to largest. Take the first 1, 2, 3 or 4 smallest values as candidates to close loop.

To use libhaloc as the second option:

File truncated at 100 lines see the full file

CHANGELOG
No CHANGELOG found.

Wiki Tutorials

This package does not provide any links to tutorials in it's rosindex metadata. You can check on the ROS Wiki Tutorials page for the package.

Package Dependencies

System Dependencies

No direct system dependencies.

Dependant Packages

Name Deps
stereo_slam

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged libhaloc at Robotics Stack Exchange

No version for distro crystal showing jade. Known supported distros are highlighted in the buttons above.
Package symbol

libhaloc package from libhaloc repo

libhaloc

ROS Distro
jade

Package Summary

Tags No category tags.
Version 0.0.1
License BSD
Build type CATKIN
Use RECOMMENDED

Repository Summary

Checkout URI https://github.com/srv/libhaloc.git
VCS Type git
VCS Version indigo
Last Updated 2016-01-21
Dev Status MAINTAINED
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Package Description

Hash-Based Loop Closing

Additional Links

Maintainers

  • Pep Lluis Negre

Authors

  • Pep Lluis Negre

libhaloc

ROS library for HAsh-based LOop Closure detection. This library provides the tools for loop closing detection based on image hashing. Image hashing consists of representing every image with a small vector (hash). Then the hash of image A can be compared with the hash of image B in a super fast way in order to determine if images are similar.

The image hashing implemented in this library is based on SIFT features so, since SIFT is invariant to scale and rotation, the image hashing will be also invariant to these properties.

The library works for both mono and stereo cameras and provides a transformation (2d for mono and 3d for stereo) when loop closures are found.

[Autonomous Robots][paper]

CITATION:

@Article{Negre Carrasco2015,
   author="Negre Carrasco, Pep Lluis
   and Bonin-Font, Francisco
   and Oliver-Codina, Gabriel",
   title="Global image signature for visual loop-closure detection",
   journal="Autonomous Robots",
   year="2015",
   pages="1--15",
   issn="1573-7527",
   doi="10.1007/s10514-015-9522-4",
   url="http://dx.doi.org/10.1007/s10514-015-9522-4"
}

How to prepare your SLAM node

Modify your CMakeLists.txt as follows:

# Add this line before catkin_package()
find_package(libhaloc REQUIRED)

# Include the libhaloc directories
include_directories(
  ${catkin_INCLUDE_DIRS}
  ${libhaloc_INCLUDE_DIRS}
  ...
  )

# Link your executable with libhaloc
target_link_libraries(your_executable_here
  ${catkin_LIBRARIES}
  ${libhaloc_LIBRARIES}
  ...
  )

Include the header in your .cpp file:

#include <libhaloc/lc.h>

How to call the library

You can use libhaloc in two different ways:

  • To generate the image hashes and then, use your own techniques to compare this hashes and retrieve the best candidates to close loop.
  • To use the full power of libhaloc to search loop closing candidates and compute the homogeneous transformation (if any).

To use libhaloc as the first option:

  • Declare your haloc object:
haloc::Hash haloc_;

  • Init your haloc object (only once):
if (!hash_.isInitialized())
   hash_.init(c_cluster_.getSift());

  • Then, for every new image you process, extract its descriptor matrix (SIFT)
cv::Mat sift;
// Use opencv to extract the SIFT matrix and then:
vector<float> current_hash = hash_.getHash(sift);

  • Now, you can store all the hashes into a table and compare it:
std::vector<float> matches;
for (uint i=0; i<my_table.size(); i++)
{
   float m = hash_.match(current_hash, my_table[i]);
   matches.push_back(matches);
}

  • Finally, sort the vector of matches from smallest to largest. Take the first 1, 2, 3 or 4 smallest values as candidates to close loop.

To use libhaloc as the second option:

File truncated at 100 lines see the full file

CHANGELOG
No CHANGELOG found.

Wiki Tutorials

This package does not provide any links to tutorials in it's rosindex metadata. You can check on the ROS Wiki Tutorials page for the package.

Package Dependencies

System Dependencies

No direct system dependencies.

Dependant Packages

Name Deps
stereo_slam

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged libhaloc at Robotics Stack Exchange

No version for distro eloquent showing jade. Known supported distros are highlighted in the buttons above.
Package symbol

libhaloc package from libhaloc repo

libhaloc

ROS Distro
jade

Package Summary

Tags No category tags.
Version 0.0.1
License BSD
Build type CATKIN
Use RECOMMENDED

Repository Summary

Checkout URI https://github.com/srv/libhaloc.git
VCS Type git
VCS Version indigo
Last Updated 2016-01-21
Dev Status MAINTAINED
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Package Description

Hash-Based Loop Closing

Additional Links

Maintainers

  • Pep Lluis Negre

Authors

  • Pep Lluis Negre

libhaloc

ROS library for HAsh-based LOop Closure detection. This library provides the tools for loop closing detection based on image hashing. Image hashing consists of representing every image with a small vector (hash). Then the hash of image A can be compared with the hash of image B in a super fast way in order to determine if images are similar.

The image hashing implemented in this library is based on SIFT features so, since SIFT is invariant to scale and rotation, the image hashing will be also invariant to these properties.

The library works for both mono and stereo cameras and provides a transformation (2d for mono and 3d for stereo) when loop closures are found.

[Autonomous Robots][paper]

CITATION:

@Article{Negre Carrasco2015,
   author="Negre Carrasco, Pep Lluis
   and Bonin-Font, Francisco
   and Oliver-Codina, Gabriel",
   title="Global image signature for visual loop-closure detection",
   journal="Autonomous Robots",
   year="2015",
   pages="1--15",
   issn="1573-7527",
   doi="10.1007/s10514-015-9522-4",
   url="http://dx.doi.org/10.1007/s10514-015-9522-4"
}

How to prepare your SLAM node

Modify your CMakeLists.txt as follows:

# Add this line before catkin_package()
find_package(libhaloc REQUIRED)

# Include the libhaloc directories
include_directories(
  ${catkin_INCLUDE_DIRS}
  ${libhaloc_INCLUDE_DIRS}
  ...
  )

# Link your executable with libhaloc
target_link_libraries(your_executable_here
  ${catkin_LIBRARIES}
  ${libhaloc_LIBRARIES}
  ...
  )

Include the header in your .cpp file:

#include <libhaloc/lc.h>

How to call the library

You can use libhaloc in two different ways:

  • To generate the image hashes and then, use your own techniques to compare this hashes and retrieve the best candidates to close loop.
  • To use the full power of libhaloc to search loop closing candidates and compute the homogeneous transformation (if any).

To use libhaloc as the first option:

  • Declare your haloc object:
haloc::Hash haloc_;

  • Init your haloc object (only once):
if (!hash_.isInitialized())
   hash_.init(c_cluster_.getSift());

  • Then, for every new image you process, extract its descriptor matrix (SIFT)
cv::Mat sift;
// Use opencv to extract the SIFT matrix and then:
vector<float> current_hash = hash_.getHash(sift);

  • Now, you can store all the hashes into a table and compare it:
std::vector<float> matches;
for (uint i=0; i<my_table.size(); i++)
{
   float m = hash_.match(current_hash, my_table[i]);
   matches.push_back(matches);
}

  • Finally, sort the vector of matches from smallest to largest. Take the first 1, 2, 3 or 4 smallest values as candidates to close loop.

To use libhaloc as the second option:

File truncated at 100 lines see the full file

CHANGELOG
No CHANGELOG found.

Wiki Tutorials

This package does not provide any links to tutorials in it's rosindex metadata. You can check on the ROS Wiki Tutorials page for the package.

Package Dependencies

System Dependencies

No direct system dependencies.

Dependant Packages

Name Deps
stereo_slam

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged libhaloc at Robotics Stack Exchange

No version for distro dashing showing jade. Known supported distros are highlighted in the buttons above.
Package symbol

libhaloc package from libhaloc repo

libhaloc

ROS Distro
jade

Package Summary

Tags No category tags.
Version 0.0.1
License BSD
Build type CATKIN
Use RECOMMENDED

Repository Summary

Checkout URI https://github.com/srv/libhaloc.git
VCS Type git
VCS Version indigo
Last Updated 2016-01-21
Dev Status MAINTAINED
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Package Description

Hash-Based Loop Closing

Additional Links

Maintainers

  • Pep Lluis Negre

Authors

  • Pep Lluis Negre

libhaloc

ROS library for HAsh-based LOop Closure detection. This library provides the tools for loop closing detection based on image hashing. Image hashing consists of representing every image with a small vector (hash). Then the hash of image A can be compared with the hash of image B in a super fast way in order to determine if images are similar.

The image hashing implemented in this library is based on SIFT features so, since SIFT is invariant to scale and rotation, the image hashing will be also invariant to these properties.

The library works for both mono and stereo cameras and provides a transformation (2d for mono and 3d for stereo) when loop closures are found.

[Autonomous Robots][paper]

CITATION:

@Article{Negre Carrasco2015,
   author="Negre Carrasco, Pep Lluis
   and Bonin-Font, Francisco
   and Oliver-Codina, Gabriel",
   title="Global image signature for visual loop-closure detection",
   journal="Autonomous Robots",
   year="2015",
   pages="1--15",
   issn="1573-7527",
   doi="10.1007/s10514-015-9522-4",
   url="http://dx.doi.org/10.1007/s10514-015-9522-4"
}

How to prepare your SLAM node

Modify your CMakeLists.txt as follows:

# Add this line before catkin_package()
find_package(libhaloc REQUIRED)

# Include the libhaloc directories
include_directories(
  ${catkin_INCLUDE_DIRS}
  ${libhaloc_INCLUDE_DIRS}
  ...
  )

# Link your executable with libhaloc
target_link_libraries(your_executable_here
  ${catkin_LIBRARIES}
  ${libhaloc_LIBRARIES}
  ...
  )

Include the header in your .cpp file:

#include <libhaloc/lc.h>

How to call the library

You can use libhaloc in two different ways:

  • To generate the image hashes and then, use your own techniques to compare this hashes and retrieve the best candidates to close loop.
  • To use the full power of libhaloc to search loop closing candidates and compute the homogeneous transformation (if any).

To use libhaloc as the first option:

  • Declare your haloc object:
haloc::Hash haloc_;

  • Init your haloc object (only once):
if (!hash_.isInitialized())
   hash_.init(c_cluster_.getSift());

  • Then, for every new image you process, extract its descriptor matrix (SIFT)
cv::Mat sift;
// Use opencv to extract the SIFT matrix and then:
vector<float> current_hash = hash_.getHash(sift);

  • Now, you can store all the hashes into a table and compare it:
std::vector<float> matches;
for (uint i=0; i<my_table.size(); i++)
{
   float m = hash_.match(current_hash, my_table[i]);
   matches.push_back(matches);
}

  • Finally, sort the vector of matches from smallest to largest. Take the first 1, 2, 3 or 4 smallest values as candidates to close loop.

To use libhaloc as the second option:

File truncated at 100 lines see the full file

CHANGELOG
No CHANGELOG found.

Wiki Tutorials

This package does not provide any links to tutorials in it's rosindex metadata. You can check on the ROS Wiki Tutorials page for the package.

Package Dependencies

System Dependencies

No direct system dependencies.

Dependant Packages

Name Deps
stereo_slam

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged libhaloc at Robotics Stack Exchange

No version for distro galactic showing jade. Known supported distros are highlighted in the buttons above.
Package symbol

libhaloc package from libhaloc repo

libhaloc

ROS Distro
jade

Package Summary

Tags No category tags.
Version 0.0.1
License BSD
Build type CATKIN
Use RECOMMENDED

Repository Summary

Checkout URI https://github.com/srv/libhaloc.git
VCS Type git
VCS Version indigo
Last Updated 2016-01-21
Dev Status MAINTAINED
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Package Description

Hash-Based Loop Closing

Additional Links

Maintainers

  • Pep Lluis Negre

Authors

  • Pep Lluis Negre

libhaloc

ROS library for HAsh-based LOop Closure detection. This library provides the tools for loop closing detection based on image hashing. Image hashing consists of representing every image with a small vector (hash). Then the hash of image A can be compared with the hash of image B in a super fast way in order to determine if images are similar.

The image hashing implemented in this library is based on SIFT features so, since SIFT is invariant to scale and rotation, the image hashing will be also invariant to these properties.

The library works for both mono and stereo cameras and provides a transformation (2d for mono and 3d for stereo) when loop closures are found.

[Autonomous Robots][paper]

CITATION:

@Article{Negre Carrasco2015,
   author="Negre Carrasco, Pep Lluis
   and Bonin-Font, Francisco
   and Oliver-Codina, Gabriel",
   title="Global image signature for visual loop-closure detection",
   journal="Autonomous Robots",
   year="2015",
   pages="1--15",
   issn="1573-7527",
   doi="10.1007/s10514-015-9522-4",
   url="http://dx.doi.org/10.1007/s10514-015-9522-4"
}

How to prepare your SLAM node

Modify your CMakeLists.txt as follows:

# Add this line before catkin_package()
find_package(libhaloc REQUIRED)

# Include the libhaloc directories
include_directories(
  ${catkin_INCLUDE_DIRS}
  ${libhaloc_INCLUDE_DIRS}
  ...
  )

# Link your executable with libhaloc
target_link_libraries(your_executable_here
  ${catkin_LIBRARIES}
  ${libhaloc_LIBRARIES}
  ...
  )

Include the header in your .cpp file:

#include <libhaloc/lc.h>

How to call the library

You can use libhaloc in two different ways:

  • To generate the image hashes and then, use your own techniques to compare this hashes and retrieve the best candidates to close loop.
  • To use the full power of libhaloc to search loop closing candidates and compute the homogeneous transformation (if any).

To use libhaloc as the first option:

  • Declare your haloc object:
haloc::Hash haloc_;

  • Init your haloc object (only once):
if (!hash_.isInitialized())
   hash_.init(c_cluster_.getSift());

  • Then, for every new image you process, extract its descriptor matrix (SIFT)
cv::Mat sift;
// Use opencv to extract the SIFT matrix and then:
vector<float> current_hash = hash_.getHash(sift);

  • Now, you can store all the hashes into a table and compare it:
std::vector<float> matches;
for (uint i=0; i<my_table.size(); i++)
{
   float m = hash_.match(current_hash, my_table[i]);
   matches.push_back(matches);
}

  • Finally, sort the vector of matches from smallest to largest. Take the first 1, 2, 3 or 4 smallest values as candidates to close loop.

To use libhaloc as the second option:

File truncated at 100 lines see the full file

CHANGELOG
No CHANGELOG found.

Wiki Tutorials

This package does not provide any links to tutorials in it's rosindex metadata. You can check on the ROS Wiki Tutorials page for the package.

Package Dependencies

System Dependencies

No direct system dependencies.

Dependant Packages

Name Deps
stereo_slam

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged libhaloc at Robotics Stack Exchange

No version for distro foxy showing jade. Known supported distros are highlighted in the buttons above.
Package symbol

libhaloc package from libhaloc repo

libhaloc

ROS Distro
jade

Package Summary

Tags No category tags.
Version 0.0.1
License BSD
Build type CATKIN
Use RECOMMENDED

Repository Summary

Checkout URI https://github.com/srv/libhaloc.git
VCS Type git
VCS Version indigo
Last Updated 2016-01-21
Dev Status MAINTAINED
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Package Description

Hash-Based Loop Closing

Additional Links

Maintainers

  • Pep Lluis Negre

Authors

  • Pep Lluis Negre

libhaloc

ROS library for HAsh-based LOop Closure detection. This library provides the tools for loop closing detection based on image hashing. Image hashing consists of representing every image with a small vector (hash). Then the hash of image A can be compared with the hash of image B in a super fast way in order to determine if images are similar.

The image hashing implemented in this library is based on SIFT features so, since SIFT is invariant to scale and rotation, the image hashing will be also invariant to these properties.

The library works for both mono and stereo cameras and provides a transformation (2d for mono and 3d for stereo) when loop closures are found.

[Autonomous Robots][paper]

CITATION:

@Article{Negre Carrasco2015,
   author="Negre Carrasco, Pep Lluis
   and Bonin-Font, Francisco
   and Oliver-Codina, Gabriel",
   title="Global image signature for visual loop-closure detection",
   journal="Autonomous Robots",
   year="2015",
   pages="1--15",
   issn="1573-7527",
   doi="10.1007/s10514-015-9522-4",
   url="http://dx.doi.org/10.1007/s10514-015-9522-4"
}

How to prepare your SLAM node

Modify your CMakeLists.txt as follows:

# Add this line before catkin_package()
find_package(libhaloc REQUIRED)

# Include the libhaloc directories
include_directories(
  ${catkin_INCLUDE_DIRS}
  ${libhaloc_INCLUDE_DIRS}
  ...
  )

# Link your executable with libhaloc
target_link_libraries(your_executable_here
  ${catkin_LIBRARIES}
  ${libhaloc_LIBRARIES}
  ...
  )

Include the header in your .cpp file:

#include <libhaloc/lc.h>

How to call the library

You can use libhaloc in two different ways:

  • To generate the image hashes and then, use your own techniques to compare this hashes and retrieve the best candidates to close loop.
  • To use the full power of libhaloc to search loop closing candidates and compute the homogeneous transformation (if any).

To use libhaloc as the first option:

  • Declare your haloc object:
haloc::Hash haloc_;

  • Init your haloc object (only once):
if (!hash_.isInitialized())
   hash_.init(c_cluster_.getSift());

  • Then, for every new image you process, extract its descriptor matrix (SIFT)
cv::Mat sift;
// Use opencv to extract the SIFT matrix and then:
vector<float> current_hash = hash_.getHash(sift);

  • Now, you can store all the hashes into a table and compare it:
std::vector<float> matches;
for (uint i=0; i<my_table.size(); i++)
{
   float m = hash_.match(current_hash, my_table[i]);
   matches.push_back(matches);
}

  • Finally, sort the vector of matches from smallest to largest. Take the first 1, 2, 3 or 4 smallest values as candidates to close loop.

To use libhaloc as the second option:

File truncated at 100 lines see the full file

CHANGELOG
No CHANGELOG found.

Wiki Tutorials

This package does not provide any links to tutorials in it's rosindex metadata. You can check on the ROS Wiki Tutorials page for the package.

Package Dependencies

System Dependencies

No direct system dependencies.

Dependant Packages

Name Deps
stereo_slam

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged libhaloc at Robotics Stack Exchange

No version for distro iron showing jade. Known supported distros are highlighted in the buttons above.
Package symbol

libhaloc package from libhaloc repo

libhaloc

ROS Distro
jade

Package Summary

Tags No category tags.
Version 0.0.1
License BSD
Build type CATKIN
Use RECOMMENDED

Repository Summary

Checkout URI https://github.com/srv/libhaloc.git
VCS Type git
VCS Version indigo
Last Updated 2016-01-21
Dev Status MAINTAINED
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Package Description

Hash-Based Loop Closing

Additional Links

Maintainers

  • Pep Lluis Negre

Authors

  • Pep Lluis Negre

libhaloc

ROS library for HAsh-based LOop Closure detection. This library provides the tools for loop closing detection based on image hashing. Image hashing consists of representing every image with a small vector (hash). Then the hash of image A can be compared with the hash of image B in a super fast way in order to determine if images are similar.

The image hashing implemented in this library is based on SIFT features so, since SIFT is invariant to scale and rotation, the image hashing will be also invariant to these properties.

The library works for both mono and stereo cameras and provides a transformation (2d for mono and 3d for stereo) when loop closures are found.

[Autonomous Robots][paper]

CITATION:

@Article{Negre Carrasco2015,
   author="Negre Carrasco, Pep Lluis
   and Bonin-Font, Francisco
   and Oliver-Codina, Gabriel",
   title="Global image signature for visual loop-closure detection",
   journal="Autonomous Robots",
   year="2015",
   pages="1--15",
   issn="1573-7527",
   doi="10.1007/s10514-015-9522-4",
   url="http://dx.doi.org/10.1007/s10514-015-9522-4"
}

How to prepare your SLAM node

Modify your CMakeLists.txt as follows:

# Add this line before catkin_package()
find_package(libhaloc REQUIRED)

# Include the libhaloc directories
include_directories(
  ${catkin_INCLUDE_DIRS}
  ${libhaloc_INCLUDE_DIRS}
  ...
  )

# Link your executable with libhaloc
target_link_libraries(your_executable_here
  ${catkin_LIBRARIES}
  ${libhaloc_LIBRARIES}
  ...
  )

Include the header in your .cpp file:

#include <libhaloc/lc.h>

How to call the library

You can use libhaloc in two different ways:

  • To generate the image hashes and then, use your own techniques to compare this hashes and retrieve the best candidates to close loop.
  • To use the full power of libhaloc to search loop closing candidates and compute the homogeneous transformation (if any).

To use libhaloc as the first option:

  • Declare your haloc object:
haloc::Hash haloc_;

  • Init your haloc object (only once):
if (!hash_.isInitialized())
   hash_.init(c_cluster_.getSift());

  • Then, for every new image you process, extract its descriptor matrix (SIFT)
cv::Mat sift;
// Use opencv to extract the SIFT matrix and then:
vector<float> current_hash = hash_.getHash(sift);

  • Now, you can store all the hashes into a table and compare it:
std::vector<float> matches;
for (uint i=0; i<my_table.size(); i++)
{
   float m = hash_.match(current_hash, my_table[i]);
   matches.push_back(matches);
}

  • Finally, sort the vector of matches from smallest to largest. Take the first 1, 2, 3 or 4 smallest values as candidates to close loop.

To use libhaloc as the second option:

File truncated at 100 lines see the full file

CHANGELOG
No CHANGELOG found.

Wiki Tutorials

This package does not provide any links to tutorials in it's rosindex metadata. You can check on the ROS Wiki Tutorials page for the package.

Package Dependencies

System Dependencies

No direct system dependencies.

Dependant Packages

Name Deps
stereo_slam

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged libhaloc at Robotics Stack Exchange

No version for distro lunar showing jade. Known supported distros are highlighted in the buttons above.
Package symbol

libhaloc package from libhaloc repo

libhaloc

ROS Distro
jade

Package Summary

Tags No category tags.
Version 0.0.1
License BSD
Build type CATKIN
Use RECOMMENDED

Repository Summary

Checkout URI https://github.com/srv/libhaloc.git
VCS Type git
VCS Version indigo
Last Updated 2016-01-21
Dev Status MAINTAINED
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Package Description

Hash-Based Loop Closing

Additional Links

Maintainers

  • Pep Lluis Negre

Authors

  • Pep Lluis Negre

libhaloc

ROS library for HAsh-based LOop Closure detection. This library provides the tools for loop closing detection based on image hashing. Image hashing consists of representing every image with a small vector (hash). Then the hash of image A can be compared with the hash of image B in a super fast way in order to determine if images are similar.

The image hashing implemented in this library is based on SIFT features so, since SIFT is invariant to scale and rotation, the image hashing will be also invariant to these properties.

The library works for both mono and stereo cameras and provides a transformation (2d for mono and 3d for stereo) when loop closures are found.

[Autonomous Robots][paper]

CITATION:

@Article{Negre Carrasco2015,
   author="Negre Carrasco, Pep Lluis
   and Bonin-Font, Francisco
   and Oliver-Codina, Gabriel",
   title="Global image signature for visual loop-closure detection",
   journal="Autonomous Robots",
   year="2015",
   pages="1--15",
   issn="1573-7527",
   doi="10.1007/s10514-015-9522-4",
   url="http://dx.doi.org/10.1007/s10514-015-9522-4"
}

How to prepare your SLAM node

Modify your CMakeLists.txt as follows:

# Add this line before catkin_package()
find_package(libhaloc REQUIRED)

# Include the libhaloc directories
include_directories(
  ${catkin_INCLUDE_DIRS}
  ${libhaloc_INCLUDE_DIRS}
  ...
  )

# Link your executable with libhaloc
target_link_libraries(your_executable_here
  ${catkin_LIBRARIES}
  ${libhaloc_LIBRARIES}
  ...
  )

Include the header in your .cpp file:

#include <libhaloc/lc.h>

How to call the library

You can use libhaloc in two different ways:

  • To generate the image hashes and then, use your own techniques to compare this hashes and retrieve the best candidates to close loop.
  • To use the full power of libhaloc to search loop closing candidates and compute the homogeneous transformation (if any).

To use libhaloc as the first option:

  • Declare your haloc object:
haloc::Hash haloc_;

  • Init your haloc object (only once):
if (!hash_.isInitialized())
   hash_.init(c_cluster_.getSift());

  • Then, for every new image you process, extract its descriptor matrix (SIFT)
cv::Mat sift;
// Use opencv to extract the SIFT matrix and then:
vector<float> current_hash = hash_.getHash(sift);

  • Now, you can store all the hashes into a table and compare it:
std::vector<float> matches;
for (uint i=0; i<my_table.size(); i++)
{
   float m = hash_.match(current_hash, my_table[i]);
   matches.push_back(matches);
}

  • Finally, sort the vector of matches from smallest to largest. Take the first 1, 2, 3 or 4 smallest values as candidates to close loop.

To use libhaloc as the second option:

File truncated at 100 lines see the full file

CHANGELOG
No CHANGELOG found.

Wiki Tutorials

This package does not provide any links to tutorials in it's rosindex metadata. You can check on the ROS Wiki Tutorials page for the package.

Package Dependencies

System Dependencies

No direct system dependencies.

Dependant Packages

Name Deps
stereo_slam

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged libhaloc at Robotics Stack Exchange

Package symbol

libhaloc package from libhaloc repo

libhaloc

ROS Distro
jade

Package Summary

Tags No category tags.
Version 0.0.1
License BSD
Build type CATKIN
Use RECOMMENDED

Repository Summary

Checkout URI https://github.com/srv/libhaloc.git
VCS Type git
VCS Version indigo
Last Updated 2016-01-21
Dev Status MAINTAINED
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Package Description

Hash-Based Loop Closing

Additional Links

Maintainers

  • Pep Lluis Negre

Authors

  • Pep Lluis Negre

libhaloc

ROS library for HAsh-based LOop Closure detection. This library provides the tools for loop closing detection based on image hashing. Image hashing consists of representing every image with a small vector (hash). Then the hash of image A can be compared with the hash of image B in a super fast way in order to determine if images are similar.

The image hashing implemented in this library is based on SIFT features so, since SIFT is invariant to scale and rotation, the image hashing will be also invariant to these properties.

The library works for both mono and stereo cameras and provides a transformation (2d for mono and 3d for stereo) when loop closures are found.

[Autonomous Robots][paper]

CITATION:

@Article{Negre Carrasco2015,
   author="Negre Carrasco, Pep Lluis
   and Bonin-Font, Francisco
   and Oliver-Codina, Gabriel",
   title="Global image signature for visual loop-closure detection",
   journal="Autonomous Robots",
   year="2015",
   pages="1--15",
   issn="1573-7527",
   doi="10.1007/s10514-015-9522-4",
   url="http://dx.doi.org/10.1007/s10514-015-9522-4"
}

How to prepare your SLAM node

Modify your CMakeLists.txt as follows:

# Add this line before catkin_package()
find_package(libhaloc REQUIRED)

# Include the libhaloc directories
include_directories(
  ${catkin_INCLUDE_DIRS}
  ${libhaloc_INCLUDE_DIRS}
  ...
  )

# Link your executable with libhaloc
target_link_libraries(your_executable_here
  ${catkin_LIBRARIES}
  ${libhaloc_LIBRARIES}
  ...
  )

Include the header in your .cpp file:

#include <libhaloc/lc.h>

How to call the library

You can use libhaloc in two different ways:

  • To generate the image hashes and then, use your own techniques to compare this hashes and retrieve the best candidates to close loop.
  • To use the full power of libhaloc to search loop closing candidates and compute the homogeneous transformation (if any).

To use libhaloc as the first option:

  • Declare your haloc object:
haloc::Hash haloc_;

  • Init your haloc object (only once):
if (!hash_.isInitialized())
   hash_.init(c_cluster_.getSift());

  • Then, for every new image you process, extract its descriptor matrix (SIFT)
cv::Mat sift;
// Use opencv to extract the SIFT matrix and then:
vector<float> current_hash = hash_.getHash(sift);

  • Now, you can store all the hashes into a table and compare it:
std::vector<float> matches;
for (uint i=0; i<my_table.size(); i++)
{
   float m = hash_.match(current_hash, my_table[i]);
   matches.push_back(matches);
}

  • Finally, sort the vector of matches from smallest to largest. Take the first 1, 2, 3 or 4 smallest values as candidates to close loop.

To use libhaloc as the second option:

File truncated at 100 lines see the full file

CHANGELOG
No CHANGELOG found.

Wiki Tutorials

This package does not provide any links to tutorials in it's rosindex metadata. You can check on the ROS Wiki Tutorials page for the package.

Package Dependencies

System Dependencies

No direct system dependencies.

Dependant Packages

Name Deps
stereo_slam

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged libhaloc at Robotics Stack Exchange

Package symbol

libhaloc package from libhaloc repo

libhaloc

ROS Distro
indigo

Package Summary

Tags No category tags.
Version 0.0.1
License BSD
Build type CATKIN
Use RECOMMENDED

Repository Summary

Checkout URI https://github.com/srv/libhaloc.git
VCS Type git
VCS Version indigo
Last Updated 2016-01-21
Dev Status MAINTAINED
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Package Description

Hash-Based Loop Closing

Additional Links

Maintainers

  • Pep Lluis Negre

Authors

  • Pep Lluis Negre

libhaloc

ROS library for HAsh-based LOop Closure detection. This library provides the tools for loop closing detection based on image hashing. Image hashing consists of representing every image with a small vector (hash). Then the hash of image A can be compared with the hash of image B in a super fast way in order to determine if images are similar.

The image hashing implemented in this library is based on SIFT features so, since SIFT is invariant to scale and rotation, the image hashing will be also invariant to these properties.

The library works for both mono and stereo cameras and provides a transformation (2d for mono and 3d for stereo) when loop closures are found.

[Autonomous Robots][paper]

CITATION:

@Article{Negre Carrasco2015,
   author="Negre Carrasco, Pep Lluis
   and Bonin-Font, Francisco
   and Oliver-Codina, Gabriel",
   title="Global image signature for visual loop-closure detection",
   journal="Autonomous Robots",
   year="2015",
   pages="1--15",
   issn="1573-7527",
   doi="10.1007/s10514-015-9522-4",
   url="http://dx.doi.org/10.1007/s10514-015-9522-4"
}

How to prepare your SLAM node

Modify your CMakeLists.txt as follows:

# Add this line before catkin_package()
find_package(libhaloc REQUIRED)

# Include the libhaloc directories
include_directories(
  ${catkin_INCLUDE_DIRS}
  ${libhaloc_INCLUDE_DIRS}
  ...
  )

# Link your executable with libhaloc
target_link_libraries(your_executable_here
  ${catkin_LIBRARIES}
  ${libhaloc_LIBRARIES}
  ...
  )

Include the header in your .cpp file:

#include <libhaloc/lc.h>

How to call the library

You can use libhaloc in two different ways:

  • To generate the image hashes and then, use your own techniques to compare this hashes and retrieve the best candidates to close loop.
  • To use the full power of libhaloc to search loop closing candidates and compute the homogeneous transformation (if any).

To use libhaloc as the first option:

  • Declare your haloc object:
haloc::Hash haloc_;

  • Init your haloc object (only once):
if (!hash_.isInitialized())
   hash_.init(c_cluster_.getSift());

  • Then, for every new image you process, extract its descriptor matrix (SIFT)
cv::Mat sift;
// Use opencv to extract the SIFT matrix and then:
vector<float> current_hash = hash_.getHash(sift);

  • Now, you can store all the hashes into a table and compare it:
std::vector<float> matches;
for (uint i=0; i<my_table.size(); i++)
{
   float m = hash_.match(current_hash, my_table[i]);
   matches.push_back(matches);
}

  • Finally, sort the vector of matches from smallest to largest. Take the first 1, 2, 3 or 4 smallest values as candidates to close loop.

To use libhaloc as the second option:

File truncated at 100 lines see the full file

CHANGELOG
No CHANGELOG found.

Wiki Tutorials

This package does not provide any links to tutorials in it's rosindex metadata. You can check on the ROS Wiki Tutorials page for the package.

Package Dependencies

System Dependencies

No direct system dependencies.

Dependant Packages

Name Deps
stereo_slam

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged libhaloc at Robotics Stack Exchange

No version for distro hydro showing jade. Known supported distros are highlighted in the buttons above.
Package symbol

libhaloc package from libhaloc repo

libhaloc

ROS Distro
jade

Package Summary

Tags No category tags.
Version 0.0.1
License BSD
Build type CATKIN
Use RECOMMENDED

Repository Summary

Checkout URI https://github.com/srv/libhaloc.git
VCS Type git
VCS Version indigo
Last Updated 2016-01-21
Dev Status MAINTAINED
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Package Description

Hash-Based Loop Closing

Additional Links

Maintainers

  • Pep Lluis Negre

Authors

  • Pep Lluis Negre

libhaloc

ROS library for HAsh-based LOop Closure detection. This library provides the tools for loop closing detection based on image hashing. Image hashing consists of representing every image with a small vector (hash). Then the hash of image A can be compared with the hash of image B in a super fast way in order to determine if images are similar.

The image hashing implemented in this library is based on SIFT features so, since SIFT is invariant to scale and rotation, the image hashing will be also invariant to these properties.

The library works for both mono and stereo cameras and provides a transformation (2d for mono and 3d for stereo) when loop closures are found.

[Autonomous Robots][paper]

CITATION:

@Article{Negre Carrasco2015,
   author="Negre Carrasco, Pep Lluis
   and Bonin-Font, Francisco
   and Oliver-Codina, Gabriel",
   title="Global image signature for visual loop-closure detection",
   journal="Autonomous Robots",
   year="2015",
   pages="1--15",
   issn="1573-7527",
   doi="10.1007/s10514-015-9522-4",
   url="http://dx.doi.org/10.1007/s10514-015-9522-4"
}

How to prepare your SLAM node

Modify your CMakeLists.txt as follows:

# Add this line before catkin_package()
find_package(libhaloc REQUIRED)

# Include the libhaloc directories
include_directories(
  ${catkin_INCLUDE_DIRS}
  ${libhaloc_INCLUDE_DIRS}
  ...
  )

# Link your executable with libhaloc
target_link_libraries(your_executable_here
  ${catkin_LIBRARIES}
  ${libhaloc_LIBRARIES}
  ...
  )

Include the header in your .cpp file:

#include <libhaloc/lc.h>

How to call the library

You can use libhaloc in two different ways:

  • To generate the image hashes and then, use your own techniques to compare this hashes and retrieve the best candidates to close loop.
  • To use the full power of libhaloc to search loop closing candidates and compute the homogeneous transformation (if any).

To use libhaloc as the first option:

  • Declare your haloc object:
haloc::Hash haloc_;

  • Init your haloc object (only once):
if (!hash_.isInitialized())
   hash_.init(c_cluster_.getSift());

  • Then, for every new image you process, extract its descriptor matrix (SIFT)
cv::Mat sift;
// Use opencv to extract the SIFT matrix and then:
vector<float> current_hash = hash_.getHash(sift);

  • Now, you can store all the hashes into a table and compare it:
std::vector<float> matches;
for (uint i=0; i<my_table.size(); i++)
{
   float m = hash_.match(current_hash, my_table[i]);
   matches.push_back(matches);
}

  • Finally, sort the vector of matches from smallest to largest. Take the first 1, 2, 3 or 4 smallest values as candidates to close loop.

To use libhaloc as the second option:

File truncated at 100 lines see the full file

CHANGELOG
No CHANGELOG found.

Wiki Tutorials

This package does not provide any links to tutorials in it's rosindex metadata. You can check on the ROS Wiki Tutorials page for the package.

Package Dependencies

System Dependencies

No direct system dependencies.

Dependant Packages

Name Deps
stereo_slam

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged libhaloc at Robotics Stack Exchange

No version for distro kinetic showing jade. Known supported distros are highlighted in the buttons above.
Package symbol

libhaloc package from libhaloc repo

libhaloc

ROS Distro
jade

Package Summary

Tags No category tags.
Version 0.0.1
License BSD
Build type CATKIN
Use RECOMMENDED

Repository Summary

Checkout URI https://github.com/srv/libhaloc.git
VCS Type git
VCS Version indigo
Last Updated 2016-01-21
Dev Status MAINTAINED
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Package Description

Hash-Based Loop Closing

Additional Links

Maintainers

  • Pep Lluis Negre

Authors

  • Pep Lluis Negre

libhaloc

ROS library for HAsh-based LOop Closure detection. This library provides the tools for loop closing detection based on image hashing. Image hashing consists of representing every image with a small vector (hash). Then the hash of image A can be compared with the hash of image B in a super fast way in order to determine if images are similar.

The image hashing implemented in this library is based on SIFT features so, since SIFT is invariant to scale and rotation, the image hashing will be also invariant to these properties.

The library works for both mono and stereo cameras and provides a transformation (2d for mono and 3d for stereo) when loop closures are found.

[Autonomous Robots][paper]

CITATION:

@Article{Negre Carrasco2015,
   author="Negre Carrasco, Pep Lluis
   and Bonin-Font, Francisco
   and Oliver-Codina, Gabriel",
   title="Global image signature for visual loop-closure detection",
   journal="Autonomous Robots",
   year="2015",
   pages="1--15",
   issn="1573-7527",
   doi="10.1007/s10514-015-9522-4",
   url="http://dx.doi.org/10.1007/s10514-015-9522-4"
}

How to prepare your SLAM node

Modify your CMakeLists.txt as follows:

# Add this line before catkin_package()
find_package(libhaloc REQUIRED)

# Include the libhaloc directories
include_directories(
  ${catkin_INCLUDE_DIRS}
  ${libhaloc_INCLUDE_DIRS}
  ...
  )

# Link your executable with libhaloc
target_link_libraries(your_executable_here
  ${catkin_LIBRARIES}
  ${libhaloc_LIBRARIES}
  ...
  )

Include the header in your .cpp file:

#include <libhaloc/lc.h>

How to call the library

You can use libhaloc in two different ways:

  • To generate the image hashes and then, use your own techniques to compare this hashes and retrieve the best candidates to close loop.
  • To use the full power of libhaloc to search loop closing candidates and compute the homogeneous transformation (if any).

To use libhaloc as the first option:

  • Declare your haloc object:
haloc::Hash haloc_;

  • Init your haloc object (only once):
if (!hash_.isInitialized())
   hash_.init(c_cluster_.getSift());

  • Then, for every new image you process, extract its descriptor matrix (SIFT)
cv::Mat sift;
// Use opencv to extract the SIFT matrix and then:
vector<float> current_hash = hash_.getHash(sift);

  • Now, you can store all the hashes into a table and compare it:
std::vector<float> matches;
for (uint i=0; i<my_table.size(); i++)
{
   float m = hash_.match(current_hash, my_table[i]);
   matches.push_back(matches);
}

  • Finally, sort the vector of matches from smallest to largest. Take the first 1, 2, 3 or 4 smallest values as candidates to close loop.

To use libhaloc as the second option:

File truncated at 100 lines see the full file

CHANGELOG
No CHANGELOG found.

Wiki Tutorials

This package does not provide any links to tutorials in it's rosindex metadata. You can check on the ROS Wiki Tutorials page for the package.

Package Dependencies

System Dependencies

No direct system dependencies.

Dependant Packages

Name Deps
stereo_slam

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged libhaloc at Robotics Stack Exchange

No version for distro melodic showing jade. Known supported distros are highlighted in the buttons above.
Package symbol

libhaloc package from libhaloc repo

libhaloc

ROS Distro
jade

Package Summary

Tags No category tags.
Version 0.0.1
License BSD
Build type CATKIN
Use RECOMMENDED

Repository Summary

Checkout URI https://github.com/srv/libhaloc.git
VCS Type git
VCS Version indigo
Last Updated 2016-01-21
Dev Status MAINTAINED
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Package Description

Hash-Based Loop Closing

Additional Links

Maintainers

  • Pep Lluis Negre

Authors

  • Pep Lluis Negre

libhaloc

ROS library for HAsh-based LOop Closure detection. This library provides the tools for loop closing detection based on image hashing. Image hashing consists of representing every image with a small vector (hash). Then the hash of image A can be compared with the hash of image B in a super fast way in order to determine if images are similar.

The image hashing implemented in this library is based on SIFT features so, since SIFT is invariant to scale and rotation, the image hashing will be also invariant to these properties.

The library works for both mono and stereo cameras and provides a transformation (2d for mono and 3d for stereo) when loop closures are found.

[Autonomous Robots][paper]

CITATION:

@Article{Negre Carrasco2015,
   author="Negre Carrasco, Pep Lluis
   and Bonin-Font, Francisco
   and Oliver-Codina, Gabriel",
   title="Global image signature for visual loop-closure detection",
   journal="Autonomous Robots",
   year="2015",
   pages="1--15",
   issn="1573-7527",
   doi="10.1007/s10514-015-9522-4",
   url="http://dx.doi.org/10.1007/s10514-015-9522-4"
}

How to prepare your SLAM node

Modify your CMakeLists.txt as follows:

# Add this line before catkin_package()
find_package(libhaloc REQUIRED)

# Include the libhaloc directories
include_directories(
  ${catkin_INCLUDE_DIRS}
  ${libhaloc_INCLUDE_DIRS}
  ...
  )

# Link your executable with libhaloc
target_link_libraries(your_executable_here
  ${catkin_LIBRARIES}
  ${libhaloc_LIBRARIES}
  ...
  )

Include the header in your .cpp file:

#include <libhaloc/lc.h>

How to call the library

You can use libhaloc in two different ways:

  • To generate the image hashes and then, use your own techniques to compare this hashes and retrieve the best candidates to close loop.
  • To use the full power of libhaloc to search loop closing candidates and compute the homogeneous transformation (if any).

To use libhaloc as the first option:

  • Declare your haloc object:
haloc::Hash haloc_;

  • Init your haloc object (only once):
if (!hash_.isInitialized())
   hash_.init(c_cluster_.getSift());

  • Then, for every new image you process, extract its descriptor matrix (SIFT)
cv::Mat sift;
// Use opencv to extract the SIFT matrix and then:
vector<float> current_hash = hash_.getHash(sift);

  • Now, you can store all the hashes into a table and compare it:
std::vector<float> matches;
for (uint i=0; i<my_table.size(); i++)
{
   float m = hash_.match(current_hash, my_table[i]);
   matches.push_back(matches);
}

  • Finally, sort the vector of matches from smallest to largest. Take the first 1, 2, 3 or 4 smallest values as candidates to close loop.

To use libhaloc as the second option:

File truncated at 100 lines see the full file

CHANGELOG
No CHANGELOG found.

Wiki Tutorials

This package does not provide any links to tutorials in it's rosindex metadata. You can check on the ROS Wiki Tutorials page for the package.

Package Dependencies

System Dependencies

No direct system dependencies.

Dependant Packages

Name Deps
stereo_slam

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged libhaloc at Robotics Stack Exchange

No version for distro noetic showing jade. Known supported distros are highlighted in the buttons above.
Package symbol

libhaloc package from libhaloc repo

libhaloc

ROS Distro
jade

Package Summary

Tags No category tags.
Version 0.0.1
License BSD
Build type CATKIN
Use RECOMMENDED

Repository Summary

Checkout URI https://github.com/srv/libhaloc.git
VCS Type git
VCS Version indigo
Last Updated 2016-01-21
Dev Status MAINTAINED
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Package Description

Hash-Based Loop Closing

Additional Links

Maintainers

  • Pep Lluis Negre

Authors

  • Pep Lluis Negre

libhaloc

ROS library for HAsh-based LOop Closure detection. This library provides the tools for loop closing detection based on image hashing. Image hashing consists of representing every image with a small vector (hash). Then the hash of image A can be compared with the hash of image B in a super fast way in order to determine if images are similar.

The image hashing implemented in this library is based on SIFT features so, since SIFT is invariant to scale and rotation, the image hashing will be also invariant to these properties.

The library works for both mono and stereo cameras and provides a transformation (2d for mono and 3d for stereo) when loop closures are found.

[Autonomous Robots][paper]

CITATION:

@Article{Negre Carrasco2015,
   author="Negre Carrasco, Pep Lluis
   and Bonin-Font, Francisco
   and Oliver-Codina, Gabriel",
   title="Global image signature for visual loop-closure detection",
   journal="Autonomous Robots",
   year="2015",
   pages="1--15",
   issn="1573-7527",
   doi="10.1007/s10514-015-9522-4",
   url="http://dx.doi.org/10.1007/s10514-015-9522-4"
}

How to prepare your SLAM node

Modify your CMakeLists.txt as follows:

# Add this line before catkin_package()
find_package(libhaloc REQUIRED)

# Include the libhaloc directories
include_directories(
  ${catkin_INCLUDE_DIRS}
  ${libhaloc_INCLUDE_DIRS}
  ...
  )

# Link your executable with libhaloc
target_link_libraries(your_executable_here
  ${catkin_LIBRARIES}
  ${libhaloc_LIBRARIES}
  ...
  )

Include the header in your .cpp file:

#include <libhaloc/lc.h>

How to call the library

You can use libhaloc in two different ways:

  • To generate the image hashes and then, use your own techniques to compare this hashes and retrieve the best candidates to close loop.
  • To use the full power of libhaloc to search loop closing candidates and compute the homogeneous transformation (if any).

To use libhaloc as the first option:

  • Declare your haloc object:
haloc::Hash haloc_;

  • Init your haloc object (only once):
if (!hash_.isInitialized())
   hash_.init(c_cluster_.getSift());

  • Then, for every new image you process, extract its descriptor matrix (SIFT)
cv::Mat sift;
// Use opencv to extract the SIFT matrix and then:
vector<float> current_hash = hash_.getHash(sift);

  • Now, you can store all the hashes into a table and compare it:
std::vector<float> matches;
for (uint i=0; i<my_table.size(); i++)
{
   float m = hash_.match(current_hash, my_table[i]);
   matches.push_back(matches);
}

  • Finally, sort the vector of matches from smallest to largest. Take the first 1, 2, 3 or 4 smallest values as candidates to close loop.

To use libhaloc as the second option:

File truncated at 100 lines see the full file

CHANGELOG
No CHANGELOG found.

Wiki Tutorials

This package does not provide any links to tutorials in it's rosindex metadata. You can check on the ROS Wiki Tutorials page for the package.

Package Dependencies

System Dependencies

No direct system dependencies.

Dependant Packages

Name Deps
stereo_slam

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged libhaloc at Robotics Stack Exchange