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

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 trac...

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Bibliographic Details
Main Authors: Trinh, Souriya, Spindler, Fabien, Marchand, Eric, Chaumette, Francois
Format: Conference Proceeding
Language:English
Subjects:
Cameras
Image edge detection
Robustness
Sensors
Solid modeling
Three-dimensional displays
Visualization
Citations: Items that cite this one
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Summary: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.
ISSN:2153-0866
DOI:10.1109/IROS.2018.8594003