Curved glide-reflection symmetry detection

2009 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2009

Volumn , Issue , 2009, Pages 1046-1053

  Lee, Seungkyu ^a   Liu, Yanxi ^a,b  

^a Department of Computer Science and Engineering ^*  (United States)

^b PENNSYLVANIA STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SCIENCE; COMPUTERS; PATTERN RECOGNITION; SOFTWARE ENGINEERING;

3-D PARAMETER; LOCAL FEATURE; REAL-WORLD IMAGE; REFLECTION SYMMETRY; SYMMETRY DETECTION;

COMPUTER VISION;

EID: 70450205045     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPRW.2009.5206814     Document Type: Conference Paper

References (18)

1. S. Carlsson. Symmetry in perspective. In European Conference on Computer Vision vol.1, pages 249-263, 1998.
2. H. Cornelius and G. Loy. Detecting bilateral symmetry in perspective. In Proceedings of International Conference on Computer Vision and Pattern Recognition Workshop, page 191, 2006.
3. D. A. Forsyth and J. Ponce. Computer Vision: A Modern Approach. Prentice Hall, August 2002.
4. T. Kanade and J. R. Kender. Mapping image properties into shape constraints: skewed symmetry, affine-transformable patterns, and the shape-from-texture paradigm. In Human and Machine Vision, pages 237-257. Academic Press, 1983.
5. A. Kuehnle. Symmetry-based recognition of vehicle rears. Pattern Recogn. Lett., 12(4):249-258, 1991.
6. Y. Lei and K. Wong. Detection and localisation of reflectional and rotational symmetry under weak perspective projection. Pattern Recognition, 32(2):167-180, 1999.
7. Y. Liu, R. Collins, and Y. Tsin. A computational model for periodic patern perception based on frieze and wallpaper groups. IEEE Transactions on Pattern Analysis and Machine Intelligence, 26(3):354-371, 2004.
8. D. G. Lowe. Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision, 60:91- 110, 2004.
9. G. Loy and J. Eklundh. Detecting symmetry and symmetric constellations of features. In European Conference on Computer Vision, pages II: 508-521, 2006.
10. M. Mancas, B. Gosselin, and B. Macq. Fast and automatic tumoral area localisation using symmetry. IEEE International Conference on Acoustics, Speech, and Signal Processing., 2:725-728, 18-23, 2005.
11. N. J. Mitra, L. J. Guibas, and M. Pauly. Partial and approximate symmetry detection for 3d geometry. ACM Trans. Graph., 25(3):560-568, 2006.
12. S. Mitra and Y. Liu. Local facial asymmetry for expression classification. In Proceedings of International Conference on Computer Vision and Pattern Recognition, volume 2, pages 889 - 894, June 2004.
13. M. Park, S. Lee, P.-C. Chen, S. Kashyap, A. A. Butt, and Y. Liu. Performance evaluation of state-of-the-art discrete symmetry detection algorithms. In Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition, pages 1-8, June 2008.
14. H. Peng, F. Long, X. Liu, S. K. Kim, and E. W. Myers. Straightening c. elegans images. Bioinformatics, pages btm569+, November 2007.
15. D. Shen, H. Ip, and E. Teoh. Robust detection of skewed symmetries. In International Conference on Pattern Recognition, pages 1010-1013, 2000.
16. O. J. O. Söderkvist. Computer vision classification of leaves from swedish trees. Master's thesis, Linkoping University, SE-581 83 Link̈oping, Sweden, September 2001. LiTH-ISYEX- 3132.
17. L. Van Gool, M. Proesmans, and T. Moons. Mirror and point symmetry under perspective skewing. In Proceedings of International Conference on Computer Vision and Pattern Recognition, pages 285-292, 1996.
18. H.Weyl. Symmetry. Princeton University Press, 1952. ISBN 0-691-02374-3.