No version for distro humble showing hydro. Known supported distros are highlighted in the buttons above.
Package Summary
Tags | No category tags. |
Version | 1.0.0 |
License | LGPL |
Build type | CATKIN |
Use | RECOMMENDED |
Repository Summary
Checkout URI | https://github.com/ipa320/cob_environment_perception.git |
VCS Type | git |
VCS Version | hydro_dev |
Last Updated | 2014-06-18 |
Dev Status | UNMAINTAINED |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
PCL feature evaluation.
Additional Links
Maintainers
- Georg Arbeiter
Authors
- Georg Arbeiter
The following explains the evaluation process and use of the different program parts and scripts
___Labeling________________________________________________________________________________________
From raw point clouds to ground-truth
___________________________________________________________________________________________________
- pcd_to_ppm:
extract the depth and rgb data of pcd files
- extract_organized_curvature:
extract min and max curvature of pcd files to ppm color image to make labeling easier
- Import rgb, depth and curvature images in GIMP to label manually
- ppm_to_pcd:
map back the labeled ppm file onto the point cloud
___Best Configuration Parameter____________________________________________________________________
Determing the best configuration fo RSD and PC for each scene
___________________________________________________________________________________________________
- generate_test_data:
generate feature values (RSD,PC,FPFH) for a list of normal and feature radius parameters
- evaluate_test_data:
evaluate the previously generated list of feature values with several config parameters of
RSD and PC. the results are saved for all combinations in a .csv file
- use OpenOffice Calc to find the best combinations
___FPFH Training___________________________________________________________________________________
Setting up SVM for FPFH classification
___________________________________________________________________________________________________
- generatePrimitives.sh + fpfh_primitives:
generate FPFH feature values for convex and concave synthetic shapes in different sizes for
all classes
- extractFeatureValues.sh + extract_feature_values:
extract FPFH feature values for all classes from the previously generated test data using the
manually labeled scenes
- reduceFeatureValues.sh + reduce_fpfh_training_data:
perform k-means to select the most discriminating histograms (about 1,000 from over 800,000)
from all available data to reduce training time of SVM
- trainSVMs.sh + fpfh_svm_trainer:
run OpenCV svm trainer in autotrainig mode using the reduced set of FPFH feature values
- evaluateFPFH.sh + feature_evaluation_fpfh:
evaluate several configuration combinations of fpfh and create .csv file
use OpenOffice Calc to find the best one
___Testing Results_________________________________________________________________________________
Get a look on the results for the best configuration
___________________________________________________________________________________________________
- feature_evaluation:
take raw and labeled pcd, set up the desired configurations and visualize the classification
results for all features
___________________________________________________________________________________________________
CHANGELOG
No CHANGELOG found.
Package Dependencies
System Dependencies
No direct system dependencies.
Dependant Packages
Name | Deps |
---|---|
cob_environment_perception |
Launch files
No launch files found
Messages
No message files found.
Services
No service files found
Plugins
No plugins found.
Recent questions tagged cob_3d_evaluation_features at Robotics Stack Exchange
No version for distro jazzy showing hydro. Known supported distros are highlighted in the buttons above.
Package Summary
Tags | No category tags. |
Version | 1.0.0 |
License | LGPL |
Build type | CATKIN |
Use | RECOMMENDED |
Repository Summary
Checkout URI | https://github.com/ipa320/cob_environment_perception.git |
VCS Type | git |
VCS Version | hydro_dev |
Last Updated | 2014-06-18 |
Dev Status | UNMAINTAINED |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
PCL feature evaluation.
Additional Links
Maintainers
- Georg Arbeiter
Authors
- Georg Arbeiter
The following explains the evaluation process and use of the different program parts and scripts
___Labeling________________________________________________________________________________________
From raw point clouds to ground-truth
___________________________________________________________________________________________________
- pcd_to_ppm:
extract the depth and rgb data of pcd files
- extract_organized_curvature:
extract min and max curvature of pcd files to ppm color image to make labeling easier
- Import rgb, depth and curvature images in GIMP to label manually
- ppm_to_pcd:
map back the labeled ppm file onto the point cloud
___Best Configuration Parameter____________________________________________________________________
Determing the best configuration fo RSD and PC for each scene
___________________________________________________________________________________________________
- generate_test_data:
generate feature values (RSD,PC,FPFH) for a list of normal and feature radius parameters
- evaluate_test_data:
evaluate the previously generated list of feature values with several config parameters of
RSD and PC. the results are saved for all combinations in a .csv file
- use OpenOffice Calc to find the best combinations
___FPFH Training___________________________________________________________________________________
Setting up SVM for FPFH classification
___________________________________________________________________________________________________
- generatePrimitives.sh + fpfh_primitives:
generate FPFH feature values for convex and concave synthetic shapes in different sizes for
all classes
- extractFeatureValues.sh + extract_feature_values:
extract FPFH feature values for all classes from the previously generated test data using the
manually labeled scenes
- reduceFeatureValues.sh + reduce_fpfh_training_data:
perform k-means to select the most discriminating histograms (about 1,000 from over 800,000)
from all available data to reduce training time of SVM
- trainSVMs.sh + fpfh_svm_trainer:
run OpenCV svm trainer in autotrainig mode using the reduced set of FPFH feature values
- evaluateFPFH.sh + feature_evaluation_fpfh:
evaluate several configuration combinations of fpfh and create .csv file
use OpenOffice Calc to find the best one
___Testing Results_________________________________________________________________________________
Get a look on the results for the best configuration
___________________________________________________________________________________________________
- feature_evaluation:
take raw and labeled pcd, set up the desired configurations and visualize the classification
results for all features
___________________________________________________________________________________________________
CHANGELOG
No CHANGELOG found.
Package Dependencies
System Dependencies
No direct system dependencies.
Dependant Packages
Name | Deps |
---|---|
cob_environment_perception |
Launch files
No launch files found
Messages
No message files found.
Services
No service files found
Plugins
No plugins found.
Recent questions tagged cob_3d_evaluation_features at Robotics Stack Exchange
No version for distro kilted showing hydro. Known supported distros are highlighted in the buttons above.
Package Summary
Tags | No category tags. |
Version | 1.0.0 |
License | LGPL |
Build type | CATKIN |
Use | RECOMMENDED |
Repository Summary
Checkout URI | https://github.com/ipa320/cob_environment_perception.git |
VCS Type | git |
VCS Version | hydro_dev |
Last Updated | 2014-06-18 |
Dev Status | UNMAINTAINED |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
PCL feature evaluation.
Additional Links
Maintainers
- Georg Arbeiter
Authors
- Georg Arbeiter
The following explains the evaluation process and use of the different program parts and scripts
___Labeling________________________________________________________________________________________
From raw point clouds to ground-truth
___________________________________________________________________________________________________
- pcd_to_ppm:
extract the depth and rgb data of pcd files
- extract_organized_curvature:
extract min and max curvature of pcd files to ppm color image to make labeling easier
- Import rgb, depth and curvature images in GIMP to label manually
- ppm_to_pcd:
map back the labeled ppm file onto the point cloud
___Best Configuration Parameter____________________________________________________________________
Determing the best configuration fo RSD and PC for each scene
___________________________________________________________________________________________________
- generate_test_data:
generate feature values (RSD,PC,FPFH) for a list of normal and feature radius parameters
- evaluate_test_data:
evaluate the previously generated list of feature values with several config parameters of
RSD and PC. the results are saved for all combinations in a .csv file
- use OpenOffice Calc to find the best combinations
___FPFH Training___________________________________________________________________________________
Setting up SVM for FPFH classification
___________________________________________________________________________________________________
- generatePrimitives.sh + fpfh_primitives:
generate FPFH feature values for convex and concave synthetic shapes in different sizes for
all classes
- extractFeatureValues.sh + extract_feature_values:
extract FPFH feature values for all classes from the previously generated test data using the
manually labeled scenes
- reduceFeatureValues.sh + reduce_fpfh_training_data:
perform k-means to select the most discriminating histograms (about 1,000 from over 800,000)
from all available data to reduce training time of SVM
- trainSVMs.sh + fpfh_svm_trainer:
run OpenCV svm trainer in autotrainig mode using the reduced set of FPFH feature values
- evaluateFPFH.sh + feature_evaluation_fpfh:
evaluate several configuration combinations of fpfh and create .csv file
use OpenOffice Calc to find the best one
___Testing Results_________________________________________________________________________________
Get a look on the results for the best configuration
___________________________________________________________________________________________________
- feature_evaluation:
take raw and labeled pcd, set up the desired configurations and visualize the classification
results for all features
___________________________________________________________________________________________________
CHANGELOG
No CHANGELOG found.
Package Dependencies
System Dependencies
No direct system dependencies.
Dependant Packages
Name | Deps |
---|---|
cob_environment_perception |
Launch files
No launch files found
Messages
No message files found.
Services
No service files found
Plugins
No plugins found.
Recent questions tagged cob_3d_evaluation_features at Robotics Stack Exchange
No version for distro rolling showing hydro. Known supported distros are highlighted in the buttons above.
Package Summary
Tags | No category tags. |
Version | 1.0.0 |
License | LGPL |
Build type | CATKIN |
Use | RECOMMENDED |
Repository Summary
Checkout URI | https://github.com/ipa320/cob_environment_perception.git |
VCS Type | git |
VCS Version | hydro_dev |
Last Updated | 2014-06-18 |
Dev Status | UNMAINTAINED |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
PCL feature evaluation.
Additional Links
Maintainers
- Georg Arbeiter
Authors
- Georg Arbeiter
The following explains the evaluation process and use of the different program parts and scripts
___Labeling________________________________________________________________________________________
From raw point clouds to ground-truth
___________________________________________________________________________________________________
- pcd_to_ppm:
extract the depth and rgb data of pcd files
- extract_organized_curvature:
extract min and max curvature of pcd files to ppm color image to make labeling easier
- Import rgb, depth and curvature images in GIMP to label manually
- ppm_to_pcd:
map back the labeled ppm file onto the point cloud
___Best Configuration Parameter____________________________________________________________________
Determing the best configuration fo RSD and PC for each scene
___________________________________________________________________________________________________
- generate_test_data:
generate feature values (RSD,PC,FPFH) for a list of normal and feature radius parameters
- evaluate_test_data:
evaluate the previously generated list of feature values with several config parameters of
RSD and PC. the results are saved for all combinations in a .csv file
- use OpenOffice Calc to find the best combinations
___FPFH Training___________________________________________________________________________________
Setting up SVM for FPFH classification
___________________________________________________________________________________________________
- generatePrimitives.sh + fpfh_primitives:
generate FPFH feature values for convex and concave synthetic shapes in different sizes for
all classes
- extractFeatureValues.sh + extract_feature_values:
extract FPFH feature values for all classes from the previously generated test data using the
manually labeled scenes
- reduceFeatureValues.sh + reduce_fpfh_training_data:
perform k-means to select the most discriminating histograms (about 1,000 from over 800,000)
from all available data to reduce training time of SVM
- trainSVMs.sh + fpfh_svm_trainer:
run OpenCV svm trainer in autotrainig mode using the reduced set of FPFH feature values
- evaluateFPFH.sh + feature_evaluation_fpfh:
evaluate several configuration combinations of fpfh and create .csv file
use OpenOffice Calc to find the best one
___Testing Results_________________________________________________________________________________
Get a look on the results for the best configuration
___________________________________________________________________________________________________
- feature_evaluation:
take raw and labeled pcd, set up the desired configurations and visualize the classification
results for all features
___________________________________________________________________________________________________
CHANGELOG
No CHANGELOG found.
Package Dependencies
System Dependencies
No direct system dependencies.
Dependant Packages
Name | Deps |
---|---|
cob_environment_perception |
Launch files
No launch files found
Messages
No message files found.
Services
No service files found
Plugins
No plugins found.
Recent questions tagged cob_3d_evaluation_features at Robotics Stack Exchange
No version for distro ardent showing hydro. Known supported distros are highlighted in the buttons above.
Package Summary
Tags | No category tags. |
Version | 1.0.0 |
License | LGPL |
Build type | CATKIN |
Use | RECOMMENDED |
Repository Summary
Checkout URI | https://github.com/ipa320/cob_environment_perception.git |
VCS Type | git |
VCS Version | hydro_dev |
Last Updated | 2014-06-18 |
Dev Status | UNMAINTAINED |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
PCL feature evaluation.
Additional Links
Maintainers
- Georg Arbeiter
Authors
- Georg Arbeiter
The following explains the evaluation process and use of the different program parts and scripts
___Labeling________________________________________________________________________________________
From raw point clouds to ground-truth
___________________________________________________________________________________________________
- pcd_to_ppm:
extract the depth and rgb data of pcd files
- extract_organized_curvature:
extract min and max curvature of pcd files to ppm color image to make labeling easier
- Import rgb, depth and curvature images in GIMP to label manually
- ppm_to_pcd:
map back the labeled ppm file onto the point cloud
___Best Configuration Parameter____________________________________________________________________
Determing the best configuration fo RSD and PC for each scene
___________________________________________________________________________________________________
- generate_test_data:
generate feature values (RSD,PC,FPFH) for a list of normal and feature radius parameters
- evaluate_test_data:
evaluate the previously generated list of feature values with several config parameters of
RSD and PC. the results are saved for all combinations in a .csv file
- use OpenOffice Calc to find the best combinations
___FPFH Training___________________________________________________________________________________
Setting up SVM for FPFH classification
___________________________________________________________________________________________________
- generatePrimitives.sh + fpfh_primitives:
generate FPFH feature values for convex and concave synthetic shapes in different sizes for
all classes
- extractFeatureValues.sh + extract_feature_values:
extract FPFH feature values for all classes from the previously generated test data using the
manually labeled scenes
- reduceFeatureValues.sh + reduce_fpfh_training_data:
perform k-means to select the most discriminating histograms (about 1,000 from over 800,000)
from all available data to reduce training time of SVM
- trainSVMs.sh + fpfh_svm_trainer:
run OpenCV svm trainer in autotrainig mode using the reduced set of FPFH feature values
- evaluateFPFH.sh + feature_evaluation_fpfh:
evaluate several configuration combinations of fpfh and create .csv file
use OpenOffice Calc to find the best one
___Testing Results_________________________________________________________________________________
Get a look on the results for the best configuration
___________________________________________________________________________________________________
- feature_evaluation:
take raw and labeled pcd, set up the desired configurations and visualize the classification
results for all features
___________________________________________________________________________________________________
CHANGELOG
No CHANGELOG found.
Package Dependencies
System Dependencies
No direct system dependencies.
Dependant Packages
Name | Deps |
---|---|
cob_environment_perception |
Launch files
No launch files found
Messages
No message files found.
Services
No service files found
Plugins
No plugins found.
Recent questions tagged cob_3d_evaluation_features at Robotics Stack Exchange
No version for distro bouncy showing hydro. Known supported distros are highlighted in the buttons above.
Package Summary
Tags | No category tags. |
Version | 1.0.0 |
License | LGPL |
Build type | CATKIN |
Use | RECOMMENDED |
Repository Summary
Checkout URI | https://github.com/ipa320/cob_environment_perception.git |
VCS Type | git |
VCS Version | hydro_dev |
Last Updated | 2014-06-18 |
Dev Status | UNMAINTAINED |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
PCL feature evaluation.
Additional Links
Maintainers
- Georg Arbeiter
Authors
- Georg Arbeiter
The following explains the evaluation process and use of the different program parts and scripts
___Labeling________________________________________________________________________________________
From raw point clouds to ground-truth
___________________________________________________________________________________________________
- pcd_to_ppm:
extract the depth and rgb data of pcd files
- extract_organized_curvature:
extract min and max curvature of pcd files to ppm color image to make labeling easier
- Import rgb, depth and curvature images in GIMP to label manually
- ppm_to_pcd:
map back the labeled ppm file onto the point cloud
___Best Configuration Parameter____________________________________________________________________
Determing the best configuration fo RSD and PC for each scene
___________________________________________________________________________________________________
- generate_test_data:
generate feature values (RSD,PC,FPFH) for a list of normal and feature radius parameters
- evaluate_test_data:
evaluate the previously generated list of feature values with several config parameters of
RSD and PC. the results are saved for all combinations in a .csv file
- use OpenOffice Calc to find the best combinations
___FPFH Training___________________________________________________________________________________
Setting up SVM for FPFH classification
___________________________________________________________________________________________________
- generatePrimitives.sh + fpfh_primitives:
generate FPFH feature values for convex and concave synthetic shapes in different sizes for
all classes
- extractFeatureValues.sh + extract_feature_values:
extract FPFH feature values for all classes from the previously generated test data using the
manually labeled scenes
- reduceFeatureValues.sh + reduce_fpfh_training_data:
perform k-means to select the most discriminating histograms (about 1,000 from over 800,000)
from all available data to reduce training time of SVM
- trainSVMs.sh + fpfh_svm_trainer:
run OpenCV svm trainer in autotrainig mode using the reduced set of FPFH feature values
- evaluateFPFH.sh + feature_evaluation_fpfh:
evaluate several configuration combinations of fpfh and create .csv file
use OpenOffice Calc to find the best one
___Testing Results_________________________________________________________________________________
Get a look on the results for the best configuration
___________________________________________________________________________________________________
- feature_evaluation:
take raw and labeled pcd, set up the desired configurations and visualize the classification
results for all features
___________________________________________________________________________________________________
CHANGELOG
No CHANGELOG found.
Package Dependencies
System Dependencies
No direct system dependencies.
Dependant Packages
Name | Deps |
---|---|
cob_environment_perception |
Launch files
No launch files found
Messages
No message files found.
Services
No service files found
Plugins
No plugins found.
Recent questions tagged cob_3d_evaluation_features at Robotics Stack Exchange
No version for distro crystal showing hydro. Known supported distros are highlighted in the buttons above.
Package Summary
Tags | No category tags. |
Version | 1.0.0 |
License | LGPL |
Build type | CATKIN |
Use | RECOMMENDED |
Repository Summary
Checkout URI | https://github.com/ipa320/cob_environment_perception.git |
VCS Type | git |
VCS Version | hydro_dev |
Last Updated | 2014-06-18 |
Dev Status | UNMAINTAINED |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
PCL feature evaluation.
Additional Links
Maintainers
- Georg Arbeiter
Authors
- Georg Arbeiter
The following explains the evaluation process and use of the different program parts and scripts
___Labeling________________________________________________________________________________________
From raw point clouds to ground-truth
___________________________________________________________________________________________________
- pcd_to_ppm:
extract the depth and rgb data of pcd files
- extract_organized_curvature:
extract min and max curvature of pcd files to ppm color image to make labeling easier
- Import rgb, depth and curvature images in GIMP to label manually
- ppm_to_pcd:
map back the labeled ppm file onto the point cloud
___Best Configuration Parameter____________________________________________________________________
Determing the best configuration fo RSD and PC for each scene
___________________________________________________________________________________________________
- generate_test_data:
generate feature values (RSD,PC,FPFH) for a list of normal and feature radius parameters
- evaluate_test_data:
evaluate the previously generated list of feature values with several config parameters of
RSD and PC. the results are saved for all combinations in a .csv file
- use OpenOffice Calc to find the best combinations
___FPFH Training___________________________________________________________________________________
Setting up SVM for FPFH classification
___________________________________________________________________________________________________
- generatePrimitives.sh + fpfh_primitives:
generate FPFH feature values for convex and concave synthetic shapes in different sizes for
all classes
- extractFeatureValues.sh + extract_feature_values:
extract FPFH feature values for all classes from the previously generated test data using the
manually labeled scenes
- reduceFeatureValues.sh + reduce_fpfh_training_data:
perform k-means to select the most discriminating histograms (about 1,000 from over 800,000)
from all available data to reduce training time of SVM
- trainSVMs.sh + fpfh_svm_trainer:
run OpenCV svm trainer in autotrainig mode using the reduced set of FPFH feature values
- evaluateFPFH.sh + feature_evaluation_fpfh:
evaluate several configuration combinations of fpfh and create .csv file
use OpenOffice Calc to find the best one
___Testing Results_________________________________________________________________________________
Get a look on the results for the best configuration
___________________________________________________________________________________________________
- feature_evaluation:
take raw and labeled pcd, set up the desired configurations and visualize the classification
results for all features
___________________________________________________________________________________________________
CHANGELOG
No CHANGELOG found.
Package Dependencies
System Dependencies
No direct system dependencies.
Dependant Packages
Name | Deps |
---|---|
cob_environment_perception |
Launch files
No launch files found
Messages
No message files found.
Services
No service files found
Plugins
No plugins found.
Recent questions tagged cob_3d_evaluation_features at Robotics Stack Exchange
No version for distro eloquent showing hydro. Known supported distros are highlighted in the buttons above.
Package Summary
Tags | No category tags. |
Version | 1.0.0 |
License | LGPL |
Build type | CATKIN |
Use | RECOMMENDED |
Repository Summary
Checkout URI | https://github.com/ipa320/cob_environment_perception.git |
VCS Type | git |
VCS Version | hydro_dev |
Last Updated | 2014-06-18 |
Dev Status | UNMAINTAINED |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
PCL feature evaluation.
Additional Links
Maintainers
- Georg Arbeiter
Authors
- Georg Arbeiter
The following explains the evaluation process and use of the different program parts and scripts
___Labeling________________________________________________________________________________________
From raw point clouds to ground-truth
___________________________________________________________________________________________________
- pcd_to_ppm:
extract the depth and rgb data of pcd files
- extract_organized_curvature:
extract min and max curvature of pcd files to ppm color image to make labeling easier
- Import rgb, depth and curvature images in GIMP to label manually
- ppm_to_pcd:
map back the labeled ppm file onto the point cloud
___Best Configuration Parameter____________________________________________________________________
Determing the best configuration fo RSD and PC for each scene
___________________________________________________________________________________________________
- generate_test_data:
generate feature values (RSD,PC,FPFH) for a list of normal and feature radius parameters
- evaluate_test_data:
evaluate the previously generated list of feature values with several config parameters of
RSD and PC. the results are saved for all combinations in a .csv file
- use OpenOffice Calc to find the best combinations
___FPFH Training___________________________________________________________________________________
Setting up SVM for FPFH classification
___________________________________________________________________________________________________
- generatePrimitives.sh + fpfh_primitives:
generate FPFH feature values for convex and concave synthetic shapes in different sizes for
all classes
- extractFeatureValues.sh + extract_feature_values:
extract FPFH feature values for all classes from the previously generated test data using the
manually labeled scenes
- reduceFeatureValues.sh + reduce_fpfh_training_data:
perform k-means to select the most discriminating histograms (about 1,000 from over 800,000)
from all available data to reduce training time of SVM
- trainSVMs.sh + fpfh_svm_trainer:
run OpenCV svm trainer in autotrainig mode using the reduced set of FPFH feature values
- evaluateFPFH.sh + feature_evaluation_fpfh:
evaluate several configuration combinations of fpfh and create .csv file
use OpenOffice Calc to find the best one
___Testing Results_________________________________________________________________________________
Get a look on the results for the best configuration
___________________________________________________________________________________________________
- feature_evaluation:
take raw and labeled pcd, set up the desired configurations and visualize the classification
results for all features
___________________________________________________________________________________________________
CHANGELOG
No CHANGELOG found.
Package Dependencies
System Dependencies
No direct system dependencies.
Dependant Packages
Name | Deps |
---|---|
cob_environment_perception |
Launch files
No launch files found
Messages
No message files found.
Services
No service files found
Plugins
No plugins found.
Recent questions tagged cob_3d_evaluation_features at Robotics Stack Exchange
No version for distro dashing showing hydro. Known supported distros are highlighted in the buttons above.
Package Summary
Tags | No category tags. |
Version | 1.0.0 |
License | LGPL |
Build type | CATKIN |
Use | RECOMMENDED |
Repository Summary
Checkout URI | https://github.com/ipa320/cob_environment_perception.git |
VCS Type | git |
VCS Version | hydro_dev |
Last Updated | 2014-06-18 |
Dev Status | UNMAINTAINED |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
PCL feature evaluation.
Additional Links
Maintainers
- Georg Arbeiter
Authors
- Georg Arbeiter
The following explains the evaluation process and use of the different program parts and scripts
___Labeling________________________________________________________________________________________
From raw point clouds to ground-truth
___________________________________________________________________________________________________
- pcd_to_ppm:
extract the depth and rgb data of pcd files
- extract_organized_curvature:
extract min and max curvature of pcd files to ppm color image to make labeling easier
- Import rgb, depth and curvature images in GIMP to label manually
- ppm_to_pcd:
map back the labeled ppm file onto the point cloud
___Best Configuration Parameter____________________________________________________________________
Determing the best configuration fo RSD and PC for each scene
___________________________________________________________________________________________________
- generate_test_data:
generate feature values (RSD,PC,FPFH) for a list of normal and feature radius parameters
- evaluate_test_data:
evaluate the previously generated list of feature values with several config parameters of
RSD and PC. the results are saved for all combinations in a .csv file
- use OpenOffice Calc to find the best combinations
___FPFH Training___________________________________________________________________________________
Setting up SVM for FPFH classification
___________________________________________________________________________________________________
- generatePrimitives.sh + fpfh_primitives:
generate FPFH feature values for convex and concave synthetic shapes in different sizes for
all classes
- extractFeatureValues.sh + extract_feature_values:
extract FPFH feature values for all classes from the previously generated test data using the
manually labeled scenes
- reduceFeatureValues.sh + reduce_fpfh_training_data:
perform k-means to select the most discriminating histograms (about 1,000 from over 800,000)
from all available data to reduce training time of SVM
- trainSVMs.sh + fpfh_svm_trainer:
run OpenCV svm trainer in autotrainig mode using the reduced set of FPFH feature values
- evaluateFPFH.sh + feature_evaluation_fpfh:
evaluate several configuration combinations of fpfh and create .csv file
use OpenOffice Calc to find the best one
___Testing Results_________________________________________________________________________________
Get a look on the results for the best configuration
___________________________________________________________________________________________________
- feature_evaluation:
take raw and labeled pcd, set up the desired configurations and visualize the classification
results for all features
___________________________________________________________________________________________________
CHANGELOG
No CHANGELOG found.
Package Dependencies
System Dependencies
No direct system dependencies.
Dependant Packages
Name | Deps |
---|---|
cob_environment_perception |
Launch files
No launch files found
Messages
No message files found.
Services
No service files found
Plugins
No plugins found.
Recent questions tagged cob_3d_evaluation_features at Robotics Stack Exchange
No version for distro galactic showing hydro. Known supported distros are highlighted in the buttons above.
Package Summary
Tags | No category tags. |
Version | 1.0.0 |
License | LGPL |
Build type | CATKIN |
Use | RECOMMENDED |
Repository Summary
Checkout URI | https://github.com/ipa320/cob_environment_perception.git |
VCS Type | git |
VCS Version | hydro_dev |
Last Updated | 2014-06-18 |
Dev Status | UNMAINTAINED |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
PCL feature evaluation.
Additional Links
Maintainers
- Georg Arbeiter
Authors
- Georg Arbeiter
The following explains the evaluation process and use of the different program parts and scripts
___Labeling________________________________________________________________________________________
From raw point clouds to ground-truth
___________________________________________________________________________________________________
- pcd_to_ppm:
extract the depth and rgb data of pcd files
- extract_organized_curvature:
extract min and max curvature of pcd files to ppm color image to make labeling easier
- Import rgb, depth and curvature images in GIMP to label manually
- ppm_to_pcd:
map back the labeled ppm file onto the point cloud
___Best Configuration Parameter____________________________________________________________________
Determing the best configuration fo RSD and PC for each scene
___________________________________________________________________________________________________
- generate_test_data:
generate feature values (RSD,PC,FPFH) for a list of normal and feature radius parameters
- evaluate_test_data:
evaluate the previously generated list of feature values with several config parameters of
RSD and PC. the results are saved for all combinations in a .csv file
- use OpenOffice Calc to find the best combinations
___FPFH Training___________________________________________________________________________________
Setting up SVM for FPFH classification
___________________________________________________________________________________________________
- generatePrimitives.sh + fpfh_primitives:
generate FPFH feature values for convex and concave synthetic shapes in different sizes for
all classes
- extractFeatureValues.sh + extract_feature_values:
extract FPFH feature values for all classes from the previously generated test data using the
manually labeled scenes
- reduceFeatureValues.sh + reduce_fpfh_training_data:
perform k-means to select the most discriminating histograms (about 1,000 from over 800,000)
from all available data to reduce training time of SVM
- trainSVMs.sh + fpfh_svm_trainer:
run OpenCV svm trainer in autotrainig mode using the reduced set of FPFH feature values
- evaluateFPFH.sh + feature_evaluation_fpfh:
evaluate several configuration combinations of fpfh and create .csv file
use OpenOffice Calc to find the best one
___Testing Results_________________________________________________________________________________
Get a look on the results for the best configuration
___________________________________________________________________________________________________
- feature_evaluation:
take raw and labeled pcd, set up the desired configurations and visualize the classification
results for all features
___________________________________________________________________________________________________
CHANGELOG
No CHANGELOG found.
Package Dependencies
System Dependencies
No direct system dependencies.
Dependant Packages
Name | Deps |
---|---|
cob_environment_perception |
Launch files
No launch files found
Messages
No message files found.
Services
No service files found
Plugins
No plugins found.
Recent questions tagged cob_3d_evaluation_features at Robotics Stack Exchange
No version for distro foxy showing hydro. Known supported distros are highlighted in the buttons above.
Package Summary
Tags | No category tags. |
Version | 1.0.0 |
License | LGPL |
Build type | CATKIN |
Use | RECOMMENDED |
Repository Summary
Checkout URI | https://github.com/ipa320/cob_environment_perception.git |
VCS Type | git |
VCS Version | hydro_dev |
Last Updated | 2014-06-18 |
Dev Status | UNMAINTAINED |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
PCL feature evaluation.
Additional Links
Maintainers
- Georg Arbeiter
Authors
- Georg Arbeiter
The following explains the evaluation process and use of the different program parts and scripts
___Labeling________________________________________________________________________________________
From raw point clouds to ground-truth
___________________________________________________________________________________________________
- pcd_to_ppm:
extract the depth and rgb data of pcd files
- extract_organized_curvature:
extract min and max curvature of pcd files to ppm color image to make labeling easier
- Import rgb, depth and curvature images in GIMP to label manually
- ppm_to_pcd:
map back the labeled ppm file onto the point cloud
___Best Configuration Parameter____________________________________________________________________
Determing the best configuration fo RSD and PC for each scene
___________________________________________________________________________________________________
- generate_test_data:
generate feature values (RSD,PC,FPFH) for a list of normal and feature radius parameters
- evaluate_test_data:
evaluate the previously generated list of feature values with several config parameters of
RSD and PC. the results are saved for all combinations in a .csv file
- use OpenOffice Calc to find the best combinations
___FPFH Training___________________________________________________________________________________
Setting up SVM for FPFH classification
___________________________________________________________________________________________________
- generatePrimitives.sh + fpfh_primitives:
generate FPFH feature values for convex and concave synthetic shapes in different sizes for
all classes
- extractFeatureValues.sh + extract_feature_values:
extract FPFH feature values for all classes from the previously generated test data using the
manually labeled scenes
- reduceFeatureValues.sh + reduce_fpfh_training_data:
perform k-means to select the most discriminating histograms (about 1,000 from over 800,000)
from all available data to reduce training time of SVM
- trainSVMs.sh + fpfh_svm_trainer:
run OpenCV svm trainer in autotrainig mode using the reduced set of FPFH feature values
- evaluateFPFH.sh + feature_evaluation_fpfh:
evaluate several configuration combinations of fpfh and create .csv file
use OpenOffice Calc to find the best one
___Testing Results_________________________________________________________________________________
Get a look on the results for the best configuration
___________________________________________________________________________________________________
- feature_evaluation:
take raw and labeled pcd, set up the desired configurations and visualize the classification
results for all features
___________________________________________________________________________________________________
CHANGELOG
No CHANGELOG found.
Package Dependencies
System Dependencies
No direct system dependencies.
Dependant Packages
Name | Deps |
---|---|
cob_environment_perception |
Launch files
No launch files found
Messages
No message files found.
Services
No service files found
Plugins
No plugins found.
Recent questions tagged cob_3d_evaluation_features at Robotics Stack Exchange
No version for distro iron showing hydro. Known supported distros are highlighted in the buttons above.
Package Summary
Tags | No category tags. |
Version | 1.0.0 |
License | LGPL |
Build type | CATKIN |
Use | RECOMMENDED |
Repository Summary
Checkout URI | https://github.com/ipa320/cob_environment_perception.git |
VCS Type | git |
VCS Version | hydro_dev |
Last Updated | 2014-06-18 |
Dev Status | UNMAINTAINED |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
PCL feature evaluation.
Additional Links
Maintainers
- Georg Arbeiter
Authors
- Georg Arbeiter
The following explains the evaluation process and use of the different program parts and scripts
___Labeling________________________________________________________________________________________
From raw point clouds to ground-truth
___________________________________________________________________________________________________
- pcd_to_ppm:
extract the depth and rgb data of pcd files
- extract_organized_curvature:
extract min and max curvature of pcd files to ppm color image to make labeling easier
- Import rgb, depth and curvature images in GIMP to label manually
- ppm_to_pcd:
map back the labeled ppm file onto the point cloud
___Best Configuration Parameter____________________________________________________________________
Determing the best configuration fo RSD and PC for each scene
___________________________________________________________________________________________________
- generate_test_data:
generate feature values (RSD,PC,FPFH) for a list of normal and feature radius parameters
- evaluate_test_data:
evaluate the previously generated list of feature values with several config parameters of
RSD and PC. the results are saved for all combinations in a .csv file
- use OpenOffice Calc to find the best combinations
___FPFH Training___________________________________________________________________________________
Setting up SVM for FPFH classification
___________________________________________________________________________________________________
- generatePrimitives.sh + fpfh_primitives:
generate FPFH feature values for convex and concave synthetic shapes in different sizes for
all classes
- extractFeatureValues.sh + extract_feature_values:
extract FPFH feature values for all classes from the previously generated test data using the
manually labeled scenes
- reduceFeatureValues.sh + reduce_fpfh_training_data:
perform k-means to select the most discriminating histograms (about 1,000 from over 800,000)
from all available data to reduce training time of SVM
- trainSVMs.sh + fpfh_svm_trainer:
run OpenCV svm trainer in autotrainig mode using the reduced set of FPFH feature values
- evaluateFPFH.sh + feature_evaluation_fpfh:
evaluate several configuration combinations of fpfh and create .csv file
use OpenOffice Calc to find the best one
___Testing Results_________________________________________________________________________________
Get a look on the results for the best configuration
___________________________________________________________________________________________________
- feature_evaluation:
take raw and labeled pcd, set up the desired configurations and visualize the classification
results for all features
___________________________________________________________________________________________________
CHANGELOG
No CHANGELOG found.
Package Dependencies
System Dependencies
No direct system dependencies.
Dependant Packages
Name | Deps |
---|---|
cob_environment_perception |
Launch files
No launch files found
Messages
No message files found.
Services
No service files found
Plugins
No plugins found.
Recent questions tagged cob_3d_evaluation_features at Robotics Stack Exchange
No version for distro lunar showing hydro. Known supported distros are highlighted in the buttons above.
Package Summary
Tags | No category tags. |
Version | 1.0.0 |
License | LGPL |
Build type | CATKIN |
Use | RECOMMENDED |
Repository Summary
Checkout URI | https://github.com/ipa320/cob_environment_perception.git |
VCS Type | git |
VCS Version | hydro_dev |
Last Updated | 2014-06-18 |
Dev Status | UNMAINTAINED |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
PCL feature evaluation.
Additional Links
Maintainers
- Georg Arbeiter
Authors
- Georg Arbeiter
The following explains the evaluation process and use of the different program parts and scripts
___Labeling________________________________________________________________________________________
From raw point clouds to ground-truth
___________________________________________________________________________________________________
- pcd_to_ppm:
extract the depth and rgb data of pcd files
- extract_organized_curvature:
extract min and max curvature of pcd files to ppm color image to make labeling easier
- Import rgb, depth and curvature images in GIMP to label manually
- ppm_to_pcd:
map back the labeled ppm file onto the point cloud
___Best Configuration Parameter____________________________________________________________________
Determing the best configuration fo RSD and PC for each scene
___________________________________________________________________________________________________
- generate_test_data:
generate feature values (RSD,PC,FPFH) for a list of normal and feature radius parameters
- evaluate_test_data:
evaluate the previously generated list of feature values with several config parameters of
RSD and PC. the results are saved for all combinations in a .csv file
- use OpenOffice Calc to find the best combinations
___FPFH Training___________________________________________________________________________________
Setting up SVM for FPFH classification
___________________________________________________________________________________________________
- generatePrimitives.sh + fpfh_primitives:
generate FPFH feature values for convex and concave synthetic shapes in different sizes for
all classes
- extractFeatureValues.sh + extract_feature_values:
extract FPFH feature values for all classes from the previously generated test data using the
manually labeled scenes
- reduceFeatureValues.sh + reduce_fpfh_training_data:
perform k-means to select the most discriminating histograms (about 1,000 from over 800,000)
from all available data to reduce training time of SVM
- trainSVMs.sh + fpfh_svm_trainer:
run OpenCV svm trainer in autotrainig mode using the reduced set of FPFH feature values
- evaluateFPFH.sh + feature_evaluation_fpfh:
evaluate several configuration combinations of fpfh and create .csv file
use OpenOffice Calc to find the best one
___Testing Results_________________________________________________________________________________
Get a look on the results for the best configuration
___________________________________________________________________________________________________
- feature_evaluation:
take raw and labeled pcd, set up the desired configurations and visualize the classification
results for all features
___________________________________________________________________________________________________
CHANGELOG
No CHANGELOG found.
Package Dependencies
System Dependencies
No direct system dependencies.
Dependant Packages
Name | Deps |
---|---|
cob_environment_perception |
Launch files
No launch files found
Messages
No message files found.
Services
No service files found
Plugins
No plugins found.
Recent questions tagged cob_3d_evaluation_features at Robotics Stack Exchange
No version for distro jade showing hydro. Known supported distros are highlighted in the buttons above.
Package Summary
Tags | No category tags. |
Version | 1.0.0 |
License | LGPL |
Build type | CATKIN |
Use | RECOMMENDED |
Repository Summary
Checkout URI | https://github.com/ipa320/cob_environment_perception.git |
VCS Type | git |
VCS Version | hydro_dev |
Last Updated | 2014-06-18 |
Dev Status | UNMAINTAINED |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
PCL feature evaluation.
Additional Links
Maintainers
- Georg Arbeiter
Authors
- Georg Arbeiter
The following explains the evaluation process and use of the different program parts and scripts
___Labeling________________________________________________________________________________________
From raw point clouds to ground-truth
___________________________________________________________________________________________________
- pcd_to_ppm:
extract the depth and rgb data of pcd files
- extract_organized_curvature:
extract min and max curvature of pcd files to ppm color image to make labeling easier
- Import rgb, depth and curvature images in GIMP to label manually
- ppm_to_pcd:
map back the labeled ppm file onto the point cloud
___Best Configuration Parameter____________________________________________________________________
Determing the best configuration fo RSD and PC for each scene
___________________________________________________________________________________________________
- generate_test_data:
generate feature values (RSD,PC,FPFH) for a list of normal and feature radius parameters
- evaluate_test_data:
evaluate the previously generated list of feature values with several config parameters of
RSD and PC. the results are saved for all combinations in a .csv file
- use OpenOffice Calc to find the best combinations
___FPFH Training___________________________________________________________________________________
Setting up SVM for FPFH classification
___________________________________________________________________________________________________
- generatePrimitives.sh + fpfh_primitives:
generate FPFH feature values for convex and concave synthetic shapes in different sizes for
all classes
- extractFeatureValues.sh + extract_feature_values:
extract FPFH feature values for all classes from the previously generated test data using the
manually labeled scenes
- reduceFeatureValues.sh + reduce_fpfh_training_data:
perform k-means to select the most discriminating histograms (about 1,000 from over 800,000)
from all available data to reduce training time of SVM
- trainSVMs.sh + fpfh_svm_trainer:
run OpenCV svm trainer in autotrainig mode using the reduced set of FPFH feature values
- evaluateFPFH.sh + feature_evaluation_fpfh:
evaluate several configuration combinations of fpfh and create .csv file
use OpenOffice Calc to find the best one
___Testing Results_________________________________________________________________________________
Get a look on the results for the best configuration
___________________________________________________________________________________________________
- feature_evaluation:
take raw and labeled pcd, set up the desired configurations and visualize the classification
results for all features
___________________________________________________________________________________________________
CHANGELOG
No CHANGELOG found.
Package Dependencies
System Dependencies
No direct system dependencies.
Dependant Packages
Name | Deps |
---|---|
cob_environment_perception |
Launch files
No launch files found
Messages
No message files found.
Services
No service files found
Plugins
No plugins found.
Recent questions tagged cob_3d_evaluation_features at Robotics Stack Exchange
No version for distro indigo showing hydro. Known supported distros are highlighted in the buttons above.
Package Summary
Tags | No category tags. |
Version | 1.0.0 |
License | LGPL |
Build type | CATKIN |
Use | RECOMMENDED |
Repository Summary
Checkout URI | https://github.com/ipa320/cob_environment_perception.git |
VCS Type | git |
VCS Version | hydro_dev |
Last Updated | 2014-06-18 |
Dev Status | UNMAINTAINED |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
PCL feature evaluation.
Additional Links
Maintainers
- Georg Arbeiter
Authors
- Georg Arbeiter
The following explains the evaluation process and use of the different program parts and scripts
___Labeling________________________________________________________________________________________
From raw point clouds to ground-truth
___________________________________________________________________________________________________
- pcd_to_ppm:
extract the depth and rgb data of pcd files
- extract_organized_curvature:
extract min and max curvature of pcd files to ppm color image to make labeling easier
- Import rgb, depth and curvature images in GIMP to label manually
- ppm_to_pcd:
map back the labeled ppm file onto the point cloud
___Best Configuration Parameter____________________________________________________________________
Determing the best configuration fo RSD and PC for each scene
___________________________________________________________________________________________________
- generate_test_data:
generate feature values (RSD,PC,FPFH) for a list of normal and feature radius parameters
- evaluate_test_data:
evaluate the previously generated list of feature values with several config parameters of
RSD and PC. the results are saved for all combinations in a .csv file
- use OpenOffice Calc to find the best combinations
___FPFH Training___________________________________________________________________________________
Setting up SVM for FPFH classification
___________________________________________________________________________________________________
- generatePrimitives.sh + fpfh_primitives:
generate FPFH feature values for convex and concave synthetic shapes in different sizes for
all classes
- extractFeatureValues.sh + extract_feature_values:
extract FPFH feature values for all classes from the previously generated test data using the
manually labeled scenes
- reduceFeatureValues.sh + reduce_fpfh_training_data:
perform k-means to select the most discriminating histograms (about 1,000 from over 800,000)
from all available data to reduce training time of SVM
- trainSVMs.sh + fpfh_svm_trainer:
run OpenCV svm trainer in autotrainig mode using the reduced set of FPFH feature values
- evaluateFPFH.sh + feature_evaluation_fpfh:
evaluate several configuration combinations of fpfh and create .csv file
use OpenOffice Calc to find the best one
___Testing Results_________________________________________________________________________________
Get a look on the results for the best configuration
___________________________________________________________________________________________________
- feature_evaluation:
take raw and labeled pcd, set up the desired configurations and visualize the classification
results for all features
___________________________________________________________________________________________________
CHANGELOG
No CHANGELOG found.
Package Dependencies
System Dependencies
No direct system dependencies.
Dependant Packages
Name | Deps |
---|---|
cob_environment_perception |
Launch files
No launch files found
Messages
No message files found.
Services
No service files found
Plugins
No plugins found.
Recent questions tagged cob_3d_evaluation_features at Robotics Stack Exchange
Package Summary
Tags | No category tags. |
Version | 1.0.0 |
License | LGPL |
Build type | CATKIN |
Use | RECOMMENDED |
Repository Summary
Checkout URI | https://github.com/ipa320/cob_environment_perception.git |
VCS Type | git |
VCS Version | hydro_dev |
Last Updated | 2014-06-18 |
Dev Status | UNMAINTAINED |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
PCL feature evaluation.
Additional Links
Maintainers
- Georg Arbeiter
Authors
- Georg Arbeiter
The following explains the evaluation process and use of the different program parts and scripts
___Labeling________________________________________________________________________________________
From raw point clouds to ground-truth
___________________________________________________________________________________________________
- pcd_to_ppm:
extract the depth and rgb data of pcd files
- extract_organized_curvature:
extract min and max curvature of pcd files to ppm color image to make labeling easier
- Import rgb, depth and curvature images in GIMP to label manually
- ppm_to_pcd:
map back the labeled ppm file onto the point cloud
___Best Configuration Parameter____________________________________________________________________
Determing the best configuration fo RSD and PC for each scene
___________________________________________________________________________________________________
- generate_test_data:
generate feature values (RSD,PC,FPFH) for a list of normal and feature radius parameters
- evaluate_test_data:
evaluate the previously generated list of feature values with several config parameters of
RSD and PC. the results are saved for all combinations in a .csv file
- use OpenOffice Calc to find the best combinations
___FPFH Training___________________________________________________________________________________
Setting up SVM for FPFH classification
___________________________________________________________________________________________________
- generatePrimitives.sh + fpfh_primitives:
generate FPFH feature values for convex and concave synthetic shapes in different sizes for
all classes
- extractFeatureValues.sh + extract_feature_values:
extract FPFH feature values for all classes from the previously generated test data using the
manually labeled scenes
- reduceFeatureValues.sh + reduce_fpfh_training_data:
perform k-means to select the most discriminating histograms (about 1,000 from over 800,000)
from all available data to reduce training time of SVM
- trainSVMs.sh + fpfh_svm_trainer:
run OpenCV svm trainer in autotrainig mode using the reduced set of FPFH feature values
- evaluateFPFH.sh + feature_evaluation_fpfh:
evaluate several configuration combinations of fpfh and create .csv file
use OpenOffice Calc to find the best one
___Testing Results_________________________________________________________________________________
Get a look on the results for the best configuration
___________________________________________________________________________________________________
- feature_evaluation:
take raw and labeled pcd, set up the desired configurations and visualize the classification
results for all features
___________________________________________________________________________________________________
CHANGELOG
No CHANGELOG found.
Package Dependencies
System Dependencies
No direct system dependencies.
Dependant Packages
Name | Deps |
---|---|
cob_environment_perception |
Launch files
No launch files found
Messages
No message files found.
Services
No service files found
Plugins
No plugins found.
Recent questions tagged cob_3d_evaluation_features at Robotics Stack Exchange
No version for distro kinetic showing hydro. Known supported distros are highlighted in the buttons above.
Package Summary
Tags | No category tags. |
Version | 1.0.0 |
License | LGPL |
Build type | CATKIN |
Use | RECOMMENDED |
Repository Summary
Checkout URI | https://github.com/ipa320/cob_environment_perception.git |
VCS Type | git |
VCS Version | hydro_dev |
Last Updated | 2014-06-18 |
Dev Status | UNMAINTAINED |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
PCL feature evaluation.
Additional Links
Maintainers
- Georg Arbeiter
Authors
- Georg Arbeiter
The following explains the evaluation process and use of the different program parts and scripts
___Labeling________________________________________________________________________________________
From raw point clouds to ground-truth
___________________________________________________________________________________________________
- pcd_to_ppm:
extract the depth and rgb data of pcd files
- extract_organized_curvature:
extract min and max curvature of pcd files to ppm color image to make labeling easier
- Import rgb, depth and curvature images in GIMP to label manually
- ppm_to_pcd:
map back the labeled ppm file onto the point cloud
___Best Configuration Parameter____________________________________________________________________
Determing the best configuration fo RSD and PC for each scene
___________________________________________________________________________________________________
- generate_test_data:
generate feature values (RSD,PC,FPFH) for a list of normal and feature radius parameters
- evaluate_test_data:
evaluate the previously generated list of feature values with several config parameters of
RSD and PC. the results are saved for all combinations in a .csv file
- use OpenOffice Calc to find the best combinations
___FPFH Training___________________________________________________________________________________
Setting up SVM for FPFH classification
___________________________________________________________________________________________________
- generatePrimitives.sh + fpfh_primitives:
generate FPFH feature values for convex and concave synthetic shapes in different sizes for
all classes
- extractFeatureValues.sh + extract_feature_values:
extract FPFH feature values for all classes from the previously generated test data using the
manually labeled scenes
- reduceFeatureValues.sh + reduce_fpfh_training_data:
perform k-means to select the most discriminating histograms (about 1,000 from over 800,000)
from all available data to reduce training time of SVM
- trainSVMs.sh + fpfh_svm_trainer:
run OpenCV svm trainer in autotrainig mode using the reduced set of FPFH feature values
- evaluateFPFH.sh + feature_evaluation_fpfh:
evaluate several configuration combinations of fpfh and create .csv file
use OpenOffice Calc to find the best one
___Testing Results_________________________________________________________________________________
Get a look on the results for the best configuration
___________________________________________________________________________________________________
- feature_evaluation:
take raw and labeled pcd, set up the desired configurations and visualize the classification
results for all features
___________________________________________________________________________________________________
CHANGELOG
No CHANGELOG found.
Package Dependencies
System Dependencies
No direct system dependencies.
Dependant Packages
Name | Deps |
---|---|
cob_environment_perception |
Launch files
No launch files found
Messages
No message files found.
Services
No service files found
Plugins
No plugins found.
Recent questions tagged cob_3d_evaluation_features at Robotics Stack Exchange
No version for distro melodic showing hydro. Known supported distros are highlighted in the buttons above.
Package Summary
Tags | No category tags. |
Version | 1.0.0 |
License | LGPL |
Build type | CATKIN |
Use | RECOMMENDED |
Repository Summary
Checkout URI | https://github.com/ipa320/cob_environment_perception.git |
VCS Type | git |
VCS Version | hydro_dev |
Last Updated | 2014-06-18 |
Dev Status | UNMAINTAINED |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
PCL feature evaluation.
Additional Links
Maintainers
- Georg Arbeiter
Authors
- Georg Arbeiter
The following explains the evaluation process and use of the different program parts and scripts
___Labeling________________________________________________________________________________________
From raw point clouds to ground-truth
___________________________________________________________________________________________________
- pcd_to_ppm:
extract the depth and rgb data of pcd files
- extract_organized_curvature:
extract min and max curvature of pcd files to ppm color image to make labeling easier
- Import rgb, depth and curvature images in GIMP to label manually
- ppm_to_pcd:
map back the labeled ppm file onto the point cloud
___Best Configuration Parameter____________________________________________________________________
Determing the best configuration fo RSD and PC for each scene
___________________________________________________________________________________________________
- generate_test_data:
generate feature values (RSD,PC,FPFH) for a list of normal and feature radius parameters
- evaluate_test_data:
evaluate the previously generated list of feature values with several config parameters of
RSD and PC. the results are saved for all combinations in a .csv file
- use OpenOffice Calc to find the best combinations
___FPFH Training___________________________________________________________________________________
Setting up SVM for FPFH classification
___________________________________________________________________________________________________
- generatePrimitives.sh + fpfh_primitives:
generate FPFH feature values for convex and concave synthetic shapes in different sizes for
all classes
- extractFeatureValues.sh + extract_feature_values:
extract FPFH feature values for all classes from the previously generated test data using the
manually labeled scenes
- reduceFeatureValues.sh + reduce_fpfh_training_data:
perform k-means to select the most discriminating histograms (about 1,000 from over 800,000)
from all available data to reduce training time of SVM
- trainSVMs.sh + fpfh_svm_trainer:
run OpenCV svm trainer in autotrainig mode using the reduced set of FPFH feature values
- evaluateFPFH.sh + feature_evaluation_fpfh:
evaluate several configuration combinations of fpfh and create .csv file
use OpenOffice Calc to find the best one
___Testing Results_________________________________________________________________________________
Get a look on the results for the best configuration
___________________________________________________________________________________________________
- feature_evaluation:
take raw and labeled pcd, set up the desired configurations and visualize the classification
results for all features
___________________________________________________________________________________________________
CHANGELOG
No CHANGELOG found.
Package Dependencies
System Dependencies
No direct system dependencies.
Dependant Packages
Name | Deps |
---|---|
cob_environment_perception |
Launch files
No launch files found
Messages
No message files found.
Services
No service files found
Plugins
No plugins found.
Recent questions tagged cob_3d_evaluation_features at Robotics Stack Exchange
No version for distro noetic showing hydro. Known supported distros are highlighted in the buttons above.
Package Summary
Tags | No category tags. |
Version | 1.0.0 |
License | LGPL |
Build type | CATKIN |
Use | RECOMMENDED |
Repository Summary
Checkout URI | https://github.com/ipa320/cob_environment_perception.git |
VCS Type | git |
VCS Version | hydro_dev |
Last Updated | 2014-06-18 |
Dev Status | UNMAINTAINED |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
PCL feature evaluation.
Additional Links
Maintainers
- Georg Arbeiter
Authors
- Georg Arbeiter
The following explains the evaluation process and use of the different program parts and scripts
___Labeling________________________________________________________________________________________
From raw point clouds to ground-truth
___________________________________________________________________________________________________
- pcd_to_ppm:
extract the depth and rgb data of pcd files
- extract_organized_curvature:
extract min and max curvature of pcd files to ppm color image to make labeling easier
- Import rgb, depth and curvature images in GIMP to label manually
- ppm_to_pcd:
map back the labeled ppm file onto the point cloud
___Best Configuration Parameter____________________________________________________________________
Determing the best configuration fo RSD and PC for each scene
___________________________________________________________________________________________________
- generate_test_data:
generate feature values (RSD,PC,FPFH) for a list of normal and feature radius parameters
- evaluate_test_data:
evaluate the previously generated list of feature values with several config parameters of
RSD and PC. the results are saved for all combinations in a .csv file
- use OpenOffice Calc to find the best combinations
___FPFH Training___________________________________________________________________________________
Setting up SVM for FPFH classification
___________________________________________________________________________________________________
- generatePrimitives.sh + fpfh_primitives:
generate FPFH feature values for convex and concave synthetic shapes in different sizes for
all classes
- extractFeatureValues.sh + extract_feature_values:
extract FPFH feature values for all classes from the previously generated test data using the
manually labeled scenes
- reduceFeatureValues.sh + reduce_fpfh_training_data:
perform k-means to select the most discriminating histograms (about 1,000 from over 800,000)
from all available data to reduce training time of SVM
- trainSVMs.sh + fpfh_svm_trainer:
run OpenCV svm trainer in autotrainig mode using the reduced set of FPFH feature values
- evaluateFPFH.sh + feature_evaluation_fpfh:
evaluate several configuration combinations of fpfh and create .csv file
use OpenOffice Calc to find the best one
___Testing Results_________________________________________________________________________________
Get a look on the results for the best configuration
___________________________________________________________________________________________________
- feature_evaluation:
take raw and labeled pcd, set up the desired configurations and visualize the classification
results for all features
___________________________________________________________________________________________________
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Dependant Packages
Name | Deps |
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cob_environment_perception |
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