Package Summary

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Version 1.0.0
License LGPL
Build type CATKIN

Repository Summary

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VCS Type git
VCS Version hydro_dev
Last Updated 2014-06-18
CI status No Continuous Integration
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Package Description

PCL feature evaluation.

Additional Links


  • Georg Arbeiter


  • Georg Arbeiter
The following explains the evaluation process and use of the different program parts and scripts


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

  - + fpfh_primitives:
    generate FPFH feature values for convex and concave synthetic shapes in different sizes for
    all classes

  - + extract_feature_values:
    extract FPFH feature values for all classes from the previously generated test data using the
    manually labeled scenes

  - + 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

  - + fpfh_svm_trainer:
    run OpenCV svm trainer in autotrainig mode using the reduced set of FPFH feature values

  - + 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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