On a cyclic string-to-string correction problem
Information Processing Letters
Introduction to algorithms
A Theory of Multiscale, Curvature-Based Shape Representation for Planar Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fundamentals of speech recognition
Fundamentals of speech recognition
Machine vision
The String-to-String Correction Problem
Journal of the ACM (JACM)
Information Retrieval
Computation of Normalized Edit Distance and Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast Computation of Normalized Edit Distances
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape Matching and Object Recognition Using Shape Contexts
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
BAS: a perceptual shape descriptor based on the beam angle statistics
Pattern Recognition Letters
Symmetry-Based Indexing of Image Databases
CBAIVL '98 Proceedings of the IEEE Workshop on Content - Based Access of Image and Video Libraries
Content-Based Image Retrieval Using Fourier Descriptors on a Logo Database
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
Digital Geometry: Geometric Methods for Digital Picture Analysis
Digital Geometry: Geometric Methods for Digital Picture Analysis
WARP: Accurate Retrieval of Shapes Using Phase of Fourier Descriptors and Time Warping Distance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Exact indexing of dynamic time warping
Knowledge and Information Systems
Shape Classification Using the Inner-Distance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape retrieval using triangle-area representation and dynamic space warping
Pattern Recognition
Introduction to Information Retrieval
Introduction to Information Retrieval
The VLDB Journal — The International Journal on Very Large Data Bases
Learning Context-Sensitive Shape Similarity by Graph Transduction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Articulation-invariant representation of non-planar shapes
ECCV'10 Proceedings of the 11th European conference on computer vision conference on Computer vision: Part III
Shape matching and classification using height functions
Pattern Recognition Letters
Beyond pairwise shape similarity analysis
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part III
The MPEG-7 visual standard for content description-an overview
IEEE Transactions on Circuits and Systems for Video Technology
MPEG-7 visual shape descriptors
IEEE Transactions on Circuits and Systems for Video Technology
A multiscale representation method for nonrigid shapes with a single closed contour
IEEE Transactions on Circuits and Systems for Video Technology
Revisiting Complex Moments for 2-D Shape Representation and Image Normalization
IEEE Transactions on Image Processing
A new geometric descriptor for symbols with affine deformations
Pattern Recognition Letters
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In recent years, in shape retrieval, methods based on dynamic time warping and sequences where each point of the contour is represented by elements of several dimensions have had a significant presence. In this approach each point of the closed contour contains information with respect to the other ones, this global information is very discriminant. The current state-of-the-art shape retrieval is based on the analysis of these distances to learn better ones. These methods are robust to noise and invariant to transformations, but, they obtain the invariance to the starting point with a brute force cyclic alignment which has a high computational time. In this work, we present cyclic dynamic time warping. It can obtain the cyclic alignment in O(n^2logn) time, where n is the size of both sequences. Experimental results show that our proposal is a better alternative than the brute force cyclic alignment and other heuristics for obtaining this invariance.