Digital image processing (2nd ed.)
Digital image processing (2nd ed.)
Photobook: content-based manipulation of image databases
International Journal of Computer Vision
Discrete Time Processing of Speech Signals
Discrete Time Processing of Speech Signals
Matching and Retrieval of Distorted and Occluded Shapes Using Dynamic Programming
IEEE Transactions on Pattern Analysis and Machine Intelligence
WARP: Accurate Retrieval of Shapes Using Phase of Fourier Descriptors and Time Warping Distance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Using the Inner-Distance for Classification of Articulated Shapes
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Shape retrieval using triangle-area representation and dynamic space warping
Pattern Recognition
A multiscale representation method for nonrigid shapes with a single closed contour
IEEE Transactions on Circuits and Systems for Video Technology
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Dynamic space warping (DSW) has emerged as a very effective tool for matching shapes. However, a central computational difficulty associated with DSW arises when a boundary's starting point (or rotation angle) is unknown. In this article, the HopDSW algorithm is proposed to speed up the starting point computation. Rather than performing an exhaustive search for the correct starting point as in classical approaches, the proposed algorithm operates in a coarse-to-fine manner. The coarse search is global and uses a hopping step to exclude points from the search. Then the search is refined in the neighborhood of the solution of the coarse search. A criterion that governs selecting the hopping step parameter is given, which reduces the number of starting point computations by an order. For shape representation, a triangle area signature (TAS) is computed from triangles formed by the boundary points. Experimental results on the MPEG-7 CE-1 database of 1400 shapes show that the proposed algorithm returns the solution to an exhaustive search with a high degree of accuracy and a considerable reduction in the number of computations.