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The International Journal of Robotics Research
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Edge-Projected Integration of Image and Model Cues for Robust Model-Based Object Tracking

M. Vincze

Institute of Flexible Automation, Vienna University of Technology, Vienna, Austriavm{at}infa.tuwien.ac.at

M. Ayromlou

W. Ponweiser

M. Zillich

Institute of Flexible Automation, Vienna University of Technology, Vienna, Austria

A real-world limitation of visual servoing approaches is the sensitivity of visual tracking to varying ambient conditions and background clutter. The authors present a model-based vision framework to improve the robustness of edge-based feature tracking. Lines and ellipses are tracked using edge-projected integration of cues (EPIC). EPIC uses cues in regions delineated by edges that are defined by observed edgels and a priori knowledge from a wire-frame model of the object. The edgels are then used for a robust fit of the feature geometry, but at times this results in multiple feature candidates. A final validation step uses the model topology to select the most likely feature candidates. EPIC is suited for real-time operation. Experiments demonstrate operation at frame rate. Navigating a walking robot through an industrial environment shows the robustness to varying lighting conditions. Tracking objects over varying backgrounds indicates robustness to clutter.

Key Words: image feature tracking • model-based • robustness • real-time • framework

The International Journal of Robotics Research, Vol. 20, No. 7, 533-552 (2001)
DOI: 10.1177/02783640122067534
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F. Martin and R. Horaud
Multiple-Camera Tracking of Rigid Objects
The International Journal of Robotics Research, February 1, 2002; 21(2): 97 - 113.
[Abstract] [PDF]