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2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (CVPR'06)
Efficient Maximally Stable Extremal Region (MSER) Tracking
New York, NY
June 17-June 22
ISBN: 0-7695-2597-0
Michael Donoser, Graz University of Technology
Horst Bischof, Graz University of Technology
This paper introduces a tracking method for the well known local MSER (Maximally Stable Extremal Region) detector. The component tree is used as an efficient data structure, which allows the calculation of MSERs in quasi-linear time. It is demonstrated that the tree is able to manage the required data for tracking. We show that by means of MSER tracking the computational time for the detection of single MSERs can be improved by a factor of 4 to 10. Using a weighted feature vector for data association improves the tracking stability. Furthermore, the component tree enables backward tracking which further improves the robustness. The novel MSER tracking algorithm is evaluated on a variety of scenes. In addition, we demonstrate three different applications, tracking of license plates, faces and fibers in paper, showing in all three scenarios improved speed and stability.
Citation:
Michael Donoser, Horst Bischof, "Efficient Maximally Stable Extremal Region (MSER) Tracking," cvpr, vol. 1, pp.553-560, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (CVPR'06), 2006
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