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.
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Li, Y., Wang, W., Gao, W. (2006). A Robust Approach for Object Recognition. In: Zhuang, Y., Yang, SQ., Rui, Y., He, Q. (eds) Advances in Multimedia Information Processing - PCM 2006. PCM 2006. Lecture Notes in Computer Science, vol 4261. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11922162_31
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DOI: https://doi.org/10.1007/11922162_31
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-48766-1
Online ISBN: 978-3-540-48769-2
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