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| Research article summary (published 29 Jun 2006): |
Real-time markerless tracking for augmented reality: the virtual visual servoing framework.
Full Abstract
Tracking is a very important research subject in a real-time augmented reality context. The main requirements for trackers are high accuracy and little latency at a reasonable cost. In order to address these issues, a real-time, robust, and efficient 3D model-based tracking algorithm is proposed for a "video see through" monocular vision system. The tracking of objects in the scene amounts to calculating the pose between the camera and the objects. Virtual objects can then be projected into the scene using the pose. Here, nonlinear pose estimation is formulated by means of a virtual visual servoing approach. In this context, the derivation of point-to-curves interaction matrices are given for different 3D geometrical primitives including straight lines, circles, cylinders, and spheres. A local moving edges tracker is used in order to provide real-time tracking of points normal to the object contours. Robustness is obtained by integrating an M-estimator into the visual control law via an iteratively reweighted least squares implementation. This approach is then extended to address the 3D model-free augmented reality problem. The method presented in this paper has been validated on several complex image sequences including outdoor environments. Results show the method to be robust to occlusion, changes in illumination, and mistracking.
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Author information
Author/s: Comport, Andrew I (AI); Marchand, Eric (E); Pressigout, Muriel (M); Chaumette, François (F);
Affiliation: IRISA-INRIA Rennes, France. Andrew.Comport(-atsign-)sophia.inria.fr
Journal and publication information
Publication Type: Evaluation Studies; Journal Article
Journal: IEEE transactions on visualization and computer graphics (IEEE Trans Vis Comput Graph), published in United States. (Language: eng)
Reference: -2006 Jul-Aug; vol 12 (issue 4) : pp 615-28
Dates: Created 2006/06/29; Completed 2006/07/27;
PMID: 16805268, status: MEDLINE (last retrieval date: 12/26/2008)
Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.
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