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15 November 2007 Relaxation-based approach for object recognition
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Proceedings Volume 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition; 67861B (2007)
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China
Object recognition can be formulated as matching image features to model features. When recognition is based on point feature, feature correspondence should be one-to-one. However, due to noises, repetitive structures and background clutters, features don't match one-to-one but one-to-many. By using the multi-scale feature point technique, we present an object recognition algorithm that makes features match one-to-one. First, it determines the correspondence by using the location, scale factor, orientation and local invariant descriptor of each feature point. Then a vote is recorded for the center, scale factor and rotation angle of object for each correspondence point. This approach can recognize the objects in the case of scale change, rotation angle changes and partial occlusion. Experimental results demonstrate the robustness of the overall approach on various image pairs.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Tongwei Lu, Xiaoying Gao, and Nong Sang "Relaxation-based approach for object recognition", Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 67861B (15 November 2007);


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