Perceptually motivated shape evolution with shape-preserving property

Pattern Recognition Letters

Volumn 31, Issue 6, 2010, Pages 447-453

  Lewin, Sergej ^a   Jiang, Xiaoyi ^a   Clausing, Achim ^a  

^a UNIVERSITY OF MÜNSTER   (Germany)

Author keywords

Shape evolution; Shape perception; Shape preservation

Indexed keywords

GAUSSIAN SMOOTHING; HEAT FLOWS; HUMAN PERCEPTION; LOCAL SHAPE; NOVEL CONCEPT; SHAPE EVOLUTION; SHAPE PERCEPTION; SHAPE PRESERVATION; SHAPE-PRESERVING PROPERTY; STEP-BY-STEP;

FACE RECOGNITION;

BIOLOGY;

EID: 77249096807     PISSN: 01678655     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patrec.2009.10.001     Document Type: Article

References (18)

1. Bai X., Yang X., Yu D., and Latecki L. Skeleton-based shape classification using path similarity. Internat. J. Pattern Recognition Artif. Intell. 22 4 (2008) 733-746
2. Biederman I. Recognition-by-components: A theory of human image understanding. Psychol. Rev. 94 2 (1987) 115-147
3. Blum H. A transformation for extracting new descriptors of form. In: Whaten-Dunn W. (Ed). Models for the Perception of Speech and Visual Form (1967), MIT Press 362-380
4. da Fontoura Costa L., and Cesar R. Shape Analysis and Classification (2001), CRC Press
5. Hoffman D., and Richards W. Parts of recognition. Cognition 18 (1985) 65-96
6. Huang Y.-P., Chang T.-W., and Sandnes F. Efficient shape-based image retrieval based on grey relational analysis and association rules. Internat. J. Pattern Recognition Artif. Intell. 22 4 (2008) 711-732
7. Jiang, X., Lewin, S., 2005. An approach to perceptual shape matching. In: Bres, S., Laurini, R. (Eds.), VISUAL, LNCS, vol. 3736, pp. 109-120.
8. Kimia B., Tannebaum A., and Zucker S. Shapes, shocks, and deformations i: The components of two-dimensional shape and the reaction-diffusion space. Internat. J. Comput. Vision 15 3 (1995) 189-224
9. Kimmel R. Numerical Geometry of Images. Theory, Algorithms and Applications (2004), Springer
10. Latecki L., and Lakämper R. Convexity rule for shape decomposition based on discrete contour evolution. Computer Vision and Image Understanding 73 3 (1999) 441-454
11. Latecki, L., Lakämper, R., Eckhardt, U., 2000. Shape descriptors for non-rigid shapes with a single closed contour. In: IEEE Conf. on Comput. Vision and Pattern Recognition, pp. 424-429.
12. Lewin, S., Jiang, X., Clausing, A., 2007. Shape evolution driven by a perceptually motivated measure. In: Bebis, G., Boyle, R.D., Parvin, B., Koracin, D., Paragios, N., Syeda-Mahmood, T.F., Ju, T., Liu, Z., Coquillart, S., Cruz-Neira, C., Müller, T., Malzbender, T. (Eds.), ISVC (2), LNCS, vol. 4842, pp. 214-223.
13. Mokhtarian F., and Bober M. Curvature Scale Space Representation: Theory, Applications & MPEG-7 Standardisation (2003), Kluwer Academic
14. Panagiotakis C., Ramasso E., Tziritas G., Rombaut M., and Pellerin D. Shape-based individual/group detection for sport videos categorization. Internat. J. Pattern Recognition Artif. Intell. 22 6 (2008) 1187-1213
15. Sapiro G. Geometric Partial Differential Equations and Image Analysis (2001), Cambridge University Press
16. Siddiqi K., and Kimia B. Parts of visual form: Computational aspects. IEEE Trans. Pattern Anal. Machine Intell. 17 3 (1995) 239-251
17. Singh M., Seyranian G., and Hoffman D. Parsing silhouettes: The short-cut rule. Percept. Psychophys. 61 4 (1999) 636-660
18. Tan, Y., Bai, X., Yang, X., Lin, L., Liu, S., Latecki, L. Skeletonization with particle filters. Internat. J. Pattern Recognition Artif. Intell., accepted for publication.