A robust approach for object recognition

Authors:
Yuanning Li;Weiqiang Wang;Wen Gao
Affiliations:
Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China;Graduate School, Chinese Academy of Sciences, Beijing, China;Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China
Venue:
PCM'06 Proceedings of the 7th Pacific Rim conference on Advances in Multimedia Information Processing
Year:
2006

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Abstract

In this paper, we present a robust and unsupervised approach for recognition of object categories, RTSI-pLSA, which overcomes the weakness of TSI-pLSA in recognizing rotated objects in images. Our approach uses radial template to describe spatial information (position, scale and orientation) of an object. A bottom up heuristical and unsupervised scheme is also proposed to estimate spatial parameters of object. Experimental results show the RTSI-pLSA can effectively recognize object categories, especially in recognizing rotated, translated, or scaled objects in images. It lowers the error rate by about 10%, compared with TSI-pLSA. Thus, it is a more robust approach for unsupervised object recognition.