Contour extraction of gait recognition based on improved GVF Snake model

Contourlet transform can be used to captures smooth contours and edges at any orientation. In order to solve the initial active contour problem of Snake model, Contourlet transform is introduced into the GVF (Gradient Vector Flow) Snake model, which will provides a way to set the initial contour, as a result, will improves the edge detection results of GVF Snake model effectively. The multi-scale decomposition is handled by a Laplacian pyramid. The directional decomposition is handled by a directional filter bank. Firstly, the contours of the object in images can be obtained based on Contourlet transform, and this contours will be identified as the initial contour of GVF Snake model. Secondly, then GVF Snake model is used to detect the contour edge of human gait motion. Experimental results show that the proposed method can extract the edge feature accurately and efficiently.

[1]  Tian Guang.  Survey of Gait Recognition , 2005 .

[2]  Lin Hong.  The Research of Background-subtraction Based Moving Objects Detection Technology , 2003 .

[3]  Xuelong Li,et al.  Image Quality Assessment Based on Multiscale Geometric Analysis , 2009, IEEE Transactions on Image Processing.

[4]  Hervé Chauris,et al.  Uniform Discrete Curvelet Transform , 2010, IEEE Transactions on Signal Processing.

[5]  Ruan Jing.  New GVF Model Based on Non-linear Diffusion , 2010 .

[6]  Junaed Sattar.  Snakes , Shapes and Gradient Vector Flow , 2022 .

[7]  Zhou He-qin.  A Motion Detection Algorithm Based on Background Subtraction and Symmetrical Differencing , 2005 .

[8]  Xavier Bresson,et al.  Geodesic Active Fields - A Geometric Framework for Image Registration , 2010 .

[9]  Demetri Terzopoulos,et al.  Snakes: Active contour models , 2004, International Journal of Computer Vision.

[10]  Jong Bae Kim,et al.  Efficient region-based motion segmentation for a video monitoring system , 2003, Pattern Recognit. Lett..

[11]  Minh N. Do,et al.  Ieee Transactions on Image Processing the Contourlet Transform: an Efficient Directional Multiresolution Image Representation , 2022 .

[12]  Qionghai Dai,et al.  Contourlet-based image quality assessment for synthesised virtual image , 2010 .

[13]  Chris J. Harris,et al.  Extracting Gait Signatures based on Anatomical Knowledge , 2002 .

[14]  Xutong Niu,et al.  A semi-automatic framework for highway extraction and vehicle detection based on a geometric deformable model , 2006 .

[15]  Jerry L. Prince,et al.  Gradient vector flow: a new external force for snakes , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[16]  Minh N. Do,et al.  Contourlets: a directional multiresolution image representation , 2002, Proceedings. International Conference on Image Processing.

[17]  A. Murat Tekalp,et al.  Digital Video Processing , 1995 .

[18]  Lily Lee,et al.  Gait analysis for classification , 2002 .

[19]  James M. Keller,et al.  Automated Geospatial Conflation of Vector Road Maps to High Resolution Imagery , 2009, IEEE Transactions on Image Processing.