IEEE Transactions on Pattern Analysis and Machine Intelligence
Dynamic Programming for Detecting, Tracking, and Matching Deformable Contours
IEEE Transactions on Pattern Analysis and Machine Intelligence
Partial surface matching by using directed footprints
Proceedings of the twelfth annual symposium on Computational geometry
IEEE Transactions on Pattern Analysis and Machine Intelligence
Matching and Retrieval of Distorted and Occluded Shapes Using Dynamic Programming
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object tracking using affine structure for point correspondences
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
A Multiscale Algorithm for Closed Contour Matching in Image Sequence
ICPR '96 Proceedings of the 1996 International Conference on Pattern Recognition (ICPR '96) Volume I - Volume 7270
Learning Chance Probability Functions for Shape Retrieval or Classification
CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 6 - Volume 06
Shape similarity search using XML and portal technology
VIP '05 Proceedings of the Pan-Sydney area workshop on Visual information processing
Shape categorization using string kernels
SSPR'06/SPR'06 Proceedings of the 2006 joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition
3-D model localization using high-resolution reconstruction of monocular image sequences
IEEE Transactions on Image Processing
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This paper presents an efficient shape matching method based on XML data, we extract the contour of the shape and this one is represented by set of points. Using corner detection method for representing the contour by a sequence of convex and concave segments. After, each segment is described by local and global features, this features are coded in string of symbols and stored in a XML file. Finally, using the dynamic programming, we find the optimal alignment between sequences of symbols. Results are presented and compared with existing methods using MATLAB for KIMIA-25 database and MPEG7 databases.