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Published in:
2006 | OriginalPaper | Chapter
A Robust Approach for Object Recognition
Authors : Yuanning Li, Weiqiang Wang, Wen Gao
Published in: Advances in Multimedia Information Processing - PCM 2006
Publisher: Springer Berlin Heidelberg
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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.