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omip: feature_tracker | joint_tracker | lgsm | rb_tracker

Package Summary

Tracker of 3-D features (up to now, only LK point features, extensible to other type of basic features) on an RGB-D stream

  • Maintainer status: maintained
  • Maintainer: Roberto Martín-Martín <roberto.martinmartin AT tu-berlin DOT de>
  • Author: Roberto Martín-Martín
  • License: MIT
  • Source: git https://github.com/tu-rbo/omip.git (branch: indigo)
omip: feature_tracker | joint_tracker | lgsm | rb_tracker

Package Summary

Tracker of 3-D features (up to now, only LK point features, extensible to other type of basic features) on an RGB-D stream

  • Maintainer status: maintained
  • Maintainer: Roberto Martín-Martín <roberto.martinmartin AT tu-berlin DOT de>
  • Author: Roberto Martín-Martín
  • License: MIT
  • Source: git https://github.com/tu-rbo/omip.git (branch: kinetic)

Caption of the feature_tracker in manual selection mode

Detailled Description

The feature_tracker package is a versatile tool to detect and track point features in a RGB-D video stream. The framework can be easily modified to use different detection & tracking algorithms. The current implementation uses Kanade-Lucas-Tomasi algorithm (opencv implementation) to first detect corner features on the first frame and then track them in consecutive frames. it maintains a constant number of features by detecting new ones.

Detection and tracking use only RGB data and provide the coordinates in image space. The 3-D Euclidean space coordinates corresponding to each tracked feature is obtained from the registered depth channel.

The feature_tracker can define a ROI between a max and a min allowed depth. It can also use an external mask that we use to define the area of the image occluded by the robot (self-occlussion mask).


2019-10-12 12:37