• DocumentCode
    2118481
  • 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
  • fYear
    2008
  • fDate
    23-28 June 2008
  • Firstpage
    1
  • Lastpage
    6
  • 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;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition Workshops, 2008. CVPRW '08. IEEE Computer Society Conference on
  • Conference_Location
    Anchorage, AK
  • ISSN
    2160-7508
  • Print_ISBN
    978-1-4244-2339-2
  • Electronic_ISBN
    2160-7508
  • Type

    conf

  • DOI
    10.1109/CVPRW.2008.4563078
  • Filename
    4563078