Only released in EOL distros:
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)
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)
Contents
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).
