A modular framework for model-based visual tracking using edge, texture and depth features

Souriya Trinh 1 Fabien Spindler 1 Eric Marchand 1 François Chaumette 1
1 RAINBOW - Sensor-based and interactive robotics
Inria Rennes – Bretagne Atlantique , IRISA-D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE
Abstract : We present in this paper a modular real-time model-based visual tracker. It is able to fuse different types of measurement, that is, edge points, textured points, and depth map, provided by one or multiple vision sensors. A confidence index is also proposed for determining if the outputs of the tracker are reliable or not. As expected, experimental results show that the more various measurements are combined, the more accurate and robust is the tracker. The corresponding C++ source code is available for the community in the ViSP library.
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Souriya Trinh, Fabien Spindler, Eric Marchand, François Chaumette. A modular framework for model-based visual tracking using edge, texture and depth features. IROS'18 - IEEE/RSJ International Conference on Intelligent Robots and Systems, Oct 2018, Madrid, Spain. pp.89-96, ⟨10.1109/IROS.2018.8594003⟩. ⟨hal-01853972⟩

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