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29 January 2007 A matching method based on valid invariant feature part
Lichun Li, Xiaohu Zhang, Qifeng Yu, Heng Zhang
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Proceedings Volume 6279, 27th International Congress on High-Speed Photography and Photonics; 62797K (2007) https://doi.org/10.1117/12.725992
Event: 27th International congress on High-Speed Photography and Photonics, 2006, Xi'an, China
Abstract
The target tracking method based on correlation in image sequence is always invalid because of the magnitude or shape distortion and occlusion. In this paper a robust and highly accuracy matching algorithm called Matching Based on Valid Invariant Feature Part (MBVF) is proposed, which combines the target image invariant feature description, matching of feature, and recognition of valid feature. The feature descriptor is formed from a vector containing the values of all the grad magnitude and orientation entries that belong to the divided parts of target area. The features is robust to image rotation, distortion, addition of noise, change in 3D viewpoint, and change in illumination. The first step of the algorithm is to build the invariant feature descriptor of the target area in the referenced image. At the second step, a coarse position of the target is calculated using the traditional forecast and correlation method. And the invariant feature descriptors of all the possible points of the tracked target in image to be tracked are built also. Next, by comparing the invariant feature of the referenced target and the tracked target the valid feature parts of the feature are recognized. At last, similitude function is calculated according the valid feature parts in both images, which give the final fine position of the target in the tracked image. Experiment results show that the MBVF can deal with the target tracking and positioning problems in image sequence process and stereo image analysis automatically and accurately.
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Lichun Li, Xiaohu Zhang, Qifeng Yu, and Heng Zhang "A matching method based on valid invariant feature part", Proc. SPIE 6279, 27th International Congress on High-Speed Photography and Photonics, 62797K (29 January 2007); https://doi.org/10.1117/12.725992
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KEYWORDS
Detection and tracking algorithms
Image processing
Distortion
Image quality
Target recognition
Algorithm development
3D acquisition
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