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Colour-Gradient Redundancy for Real-time Spatial Pose Tracking in Autonomous Robot Navigation
Quebec City, Quebec, Canada June 07-June 09
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CRV.2006.22The 3rd Canadian Conference on Comput ...
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Hans de Ruiter, University of Toronto, Canada
Beno Benhabib, University of Toronto, Canada

Mobile-robot interception or rendezvous with a maneuvering target requires the target?s pose to be tracked. This paper presents a novel 6 degree-of-freedom pose tracking algorithm. This algorithm incorporates an initial-pose estimation scheme to initiate tracking, operates in real-time, and, is robust to large motions.

Initial-pose estimation is performed using the on-screen position and size of the target to extract 3D position, and, Principal Component Analysis (PCA) to extract orientation. Real-time operation is achieved by using GPU-based filters and a novel data-reduction algorithm. This data reduction algorithm exploits an important property of colour images, namely, that the gradients of all colour channels are generally aligned. A processing rate of approximately 60 to 85 fps was obtained. Multi-scale optical-flow has been adapted for use in the tracker, to increase robustness to larger motions.

Index Terms:
computer vision, object tracking, mobile-robot navigation
Citation:
Hans de Ruiter, Beno Benhabib, "Colour-Gradient Redundancy for Real-time Spatial Pose Tracking in Autonomous Robot Navigation," crv, pp.20, The 3rd Canadian Conference on Computer and Robot Vision (CRV'06), 2006
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