Title :
Efficient partial shape matching using Smith-Waterman algorithm
Author :
Chen, Longbin ; Feris, Rogerio ; Turk, Matthew
Author_Institution :
Comput. Sci., Univ. of California, Santa Barbara, CA
Abstract :
This paper presents an efficient partial shape matching method based on the Smith-Waterman algorithm. For two contours of m and n points respectively, the complexity of our method to find similar parts is only O(mn). In addition to this improvement in efficiency, we also obtain comparable accurate matching with fewer shape descriptors. Also, in contrast to arbitrary distance functions that are used by previous methods, we use a probabilistic similarity measurement, p-value, to evaluate the similarity of two shapes. Our experiments on several public shape databases indicate that our method outperforms state-of-the-art global and partial shape matching algorithms in various scenarios.
Keywords :
computational complexity; image matching; probability; Smith-Waterman algorithm; computational complexity; partial shape matching; probabilistic similarity measurement; Computer vision; Content based retrieval; Databases; Design optimization; Image retrieval; Object recognition; Shape measurement; Skeleton; Stereo vision; Turning;
Conference_Titel :
Computer Vision and Pattern Recognition Workshops, 2008. CVPRW '08. IEEE Computer Society Conference on
Conference_Location :
Anchorage, AK
Print_ISBN :
978-1-4244-2339-2
Electronic_ISBN :
2160-7508
DOI :
10.1109/CVPRW.2008.4563078