Shape Profile Matching and Its Applications

The focus of this paper is on the development of a novel cross correlation technique for shape matching between two similar objects. The shape profile is derived from the curvature of the object profile. The cross correlation technique is applied to the shape profile of the two image objects to evaluate their similarity. An application of the shape profile technique is presented in the context of pose detection of human models from image sequences or videos. To extract the feature points on the human model, a number of human motion templates are constructed with designated feature points on each of the human motion profiles. The human model feature extraction procedure is divided into two steps, including: (1) pre-process and construction of motion templates, and (2) extraction of feature points. The best matched template image pairs and best fitted feature points are identified by evaluating the cross correlation coefficient of the corresponding shape profiles. The proposed method is demonstrated by experimental results.

[1]  D. Newland.  An introduction to random vibrations and spectral analysis , 1975 .

[2]  J. Aggarwal,et al.  Lower limb kinematics of human walking with the medial axis transformation , 1994, Proceedings of 1994 IEEE Workshop on Motion of Non-rigid and Articulated Objects.

[4]  Matthew Ming Fai Yuen,et al.  Feature-based reverse engineering of mannequin for garment design , 1999, Comput. Aided Des..

[5]  King-Sun Fu,et al.  Shape Discrimination Using Fourier Descriptors , 1977, IEEE Trans. Syst. Man Cybern..

[6]  R. A. Leibler,et al.  On Information and Sufficiency , 1951 .

[7]  Nick Barnes,et al.  An MRF and Gaussian Curvature Based Shape Representation for Shape Matching , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[8]  Tao Chen,et al.  Planar Shape Matching and Feature Extraction Using Shape Profile , 2008, GMP.

[9]  Ka Kit Chang.  Human model reconstruction from image sequence , 2003 .

[10]  William C. Regli,et al.  Using shape distributions to compare solid models , 2002, SMA '02.

[11]  Sadegh Abbasi,et al.  Shape similarity retrieval under affine transform: application to multi-view object representation and recognition , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[12]  Farzin Mokhtarian,et al.  An Efficient Active Contour Model Through Curvature Scale Space Filtering , 2004, Multimedia Tools and Applications.

[13]  Farzin Mokhtarian,et al.  A Theory of Multiscale, Curvature-Based Shape Representation for Planar Curves , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[14]  Helen C. Shen,et al.  A 3D Reconstruction System for Human Body Modeling , 1998, CAPTECH.

[15]  A. Lynn Abbott,et al.  A Shape Representation for Planar Curves by Shape Signature Harmonic Embedding , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[16]  Jitendra Malik,et al.  Shape matching and object recognition using shape contexts , 2010, 2010 3rd International Conference on Computer Science and Information Technology.

[17]  Nadia Magnenat-Thalmann,et al.  Generating Animatable 3D Virtual Humans from Photographs , 2000, Comput. Graph. Forum.

[18]  Ioannis Pitas,et al.  Digital Image Processing Algorithms and Applications , 2000 .

[19]  Mokhtarian,et al.  Curvature scale space for image point feature detection , 1999 .

[20]  M. Baroni,et al.  Assessing LV wall motion by frame-to-frame curvature matching and optical flow estimation , 1991, [1991] Proceedings Computers in Cardiology.

[21]  Dariu Gavrila,et al.  A Bayesian, Exemplar-Based Approach to Hierarchical Shape Matching , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[22]  Stefano Soatto,et al.  Integral Invariant Signatures , 2004, ECCV.

[23]  Chin-Chen Chang,et al.  Hand pose recognition using curvature scale space , 2002, Object recognition supported by user interaction for service robots.

[24]  Ralph Roskies,et al.  Fourier Descriptors for Plane Closed Curves , 1972, IEEE Transactions on Computers.