Cross-view gait recognition based on human walking trajectory

3-D gravity center track can be constructed by single-view gait sequence.View variance can be realized without gaps based on projection principle.View can be calculated directly without classification and cluster.Viewing angle labeled in current gait database can be taken as cubic view. We propose in this paper a novel cross-view gait recognition method based on projection of gravity center trajectory (GCT). We project the coefficients of 3-D GCT in reality to different view planes to complete view variation. Firstly, we estimate the real GCT curve in 3-D space under different views by statistics of limb parameters. Then, we get the view transformation matrix based on the projection principle between curve and plane, and estimate the view of a silhouette sequence by this matrix to complete view variance of gait features. We calculate the body part trajectory on silhouette sequence to improve recognition accuracy by using correlation strength as similarity measure. Lastly, we take nested match method to calculate the final matching score of two kinds of features. Experimental results on the widely used CASIA-B gait database demonstrate the effectiveness and practicability of the proposed method.

[1]  Jiwen Lu,et al.  Joint Subspace Learning for View-Invariant Gait Recognition , 2011, IEEE Signal Processing Letters.

[2]  Qiang Wu,et al.  Gait Recognition Under Various Viewing Angles Based on Correlated Motion Regression , 2012, IEEE Transactions on Circuits and Systems for Video Technology.

[3]  Osama Masoud,et al.  View-independent human motion classification using image-based reconstruction , 2009, Image Vis. Comput..

[4]  Yohan Dupuis,et al.  Feature subset selection applied to model-free gait recognition , 2013, Image Vis. Comput..

[5]  Tieniu Tan,et al.  Robust view transformation model for gait recognition , 2011, 2011 18th IEEE International Conference on Image Processing.

[6]  Qiang Wu,et al.  Support vector regression for multi-view gait recognition based on local motion feature selection , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[7]  Yunhong Wang,et al.  Multi-view multi-stance gait identification , 2011, 2011 18th IEEE International Conference on Image Processing.

[8]  Raymond S. T. Lee,et al.  Human Identification by Using the Motion and Static Characteristic of Gait , 2006, 18th International Conference on Pattern Recognition (ICPR'06).

[9]  Trevor Darrell,et al.  Integrated face and gait recognition from multiple views , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[10]  Shaogang Gong,et al.  Gait recognition without subject cooperation , 2010, Pattern Recognit. Lett..

[11]  Bir Bhanu,et al.  Individual recognition using gait energy image , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[12]  Yap-Peng Tan,et al.  View invariant gait recognition , 2010, 2010 IEEE International Conference on Acoustics, Speech and Signal Processing.

[13]  Rama Chellappa,et al.  Towards a view invariant gait recognition algorithm , 2003, Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance, 2003..

[14]  Tardi Tjahjadi,et al.  Silhouette-based gait recognition using Procrustes shape analysis and elliptic Fourier descriptors , 2012, Pattern Recognit..

[15]  Mark S. Nixon,et al.  Automatic extraction and description of human gait models for recognition purposes , 2003, Comput. Vis. Image Underst..

[16]  Shaogang Gong,et al.  Cross View Gait Recognition Using Correlation Strength , 2010, BMVC.

[17]  M. Lee,et al.  The University of Southampton Multi-Biometric Tunnel and introducing a novel 3D gait dataset , 2008, 2008 IEEE Second International Conference on Biometrics: Theory, Applications and Systems.

[18]  Jiwen Lu,et al.  Uncorrelated discriminant simplex analysis for view-invariant gait signal computing , 2010, Pattern Recognit. Lett..

[19]  Yasushi Makihara,et al.  Gait Recognition Using a View Transformation Model in the Frequency Domain , 2006, ECCV.

[20]  Haifeng Hu,et al.  Enhanced Gabor Feature Based Classification Using a Regularized Locally Tensor Discriminant Model for Multiview Gait Recognition , 2013, IEEE Transactions on Circuits and Systems for Video Technology.

[21]  Junxia Gu,et al.  Action and Gait Recognition From Recovered 3-D Human Joints , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[22]  Jun Yu,et al.  Click Prediction for Web Image Reranking Using Multimodal Sparse Coding , 2014, IEEE Transactions on Image Processing.

[23]  Sudeep Sarkar,et al.  The humanID gait challenge problem: data sets, performance, and analysis , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[24]  Haifeng Hu,et al.  Multiview Gait Recognition Based on Patch Distribution Features and Uncorrelated Multilinear Sparse Local Discriminant Canonical Correlation Analysis , 2014, IEEE Transactions on Circuits and Systems for Video Technology.

[25]  Qiang Wu,et al.  A New View-Invariant Feature for Cross-View Gait Recognition , 2013, IEEE Transactions on Information Forensics and Security.

[26]  Nikolaus F. Troje,et al.  View-independent person identification from human gait , 2005, Neurocomputing.

[27]  Tieniu Tan,et al.  A Framework for Evaluating the Effect of View Angle, Clothing and Carrying Condition on Gait Recognition , 2006, 18th International Conference on Pattern Recognition (ICPR'06).

[28]  Nikolaos V. Boulgouris,et al.  Gait Recognition With Shifted Energy Image and Structural Feature Extraction , 2012, IEEE Transactions on Image Processing.

[29]  Jun Yu,et al.  Exploiting Click Constraints and Multi-view Features for Image Re-ranking , 2014, IEEE Transactions on Multimedia.

[30]  Stefano Soatto,et al.  Recognition of human gaits , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[31]  Qiang Wu,et al.  Multiple views gait recognition using View Transformation Model based on optimized Gait Energy Image , 2009, 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops.

[32]  Mark S. Nixon,et al.  Model-Based Feature Extraction for Gait Analysis and Recognition , 2007, MIRAGE.

[33]  Robert Bergevin,et al.  Computing and evaluating view-normalized body part trajectories , 2009, Image Vis. Comput..

[34]  Amit K. Roy-Chowdhury,et al.  A study on view-insensitive gait recognition , 2005, IEEE International Conference on Image Processing 2005.

[35]  Yasushi Makihara,et al.  The largest inertial sensor-based gait database and performance evaluation of gait-based personal authentication , 2014, Pattern Recognit..

[36]  Tieniu Tan,et al.  Silhouette Analysis-Based Gait Recognition for Human Identification , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[37]  Max A. Viergever,et al.  Automatic scoliosis detection based on local centroids evaluation on moire topographic images of human backs , 2001, IEEE Transactions on Medical Imaging.

[38]  Mark S. Nixon,et al.  Exploratory factor analysis of gait recognition , 2008, 2008 8th IEEE International Conference on Automatic Face & Gesture Recognition.

[39]  Mark S. Nixon,et al.  Self-Calibrating View-Invariant Gait Biometrics , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[40]  Hua Li,et al.  3D gait recognition using multiple cameras , 2006, 7th International Conference on Automatic Face and Gesture Recognition (FGR06).

[41]  Yuan Yan Tang,et al.  High-Order Distance-Based Multiview Stochastic Learning in Image Classification , 2014, IEEE Transactions on Cybernetics.

[42]  Aaron F. Bobick,et al.  Gait recognition from time-normalized joint-angle trajectories in the walking plane , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[43]  Qiang Wu,et al.  Cross-view and multi-view gait recognitions based on view transformation model using multi-layer perceptron , 2012, Pattern Recognit. Lett..

[44]  Hassan Foroosh,et al.  View invariant action recognition using projective depth , 2014, Comput. Vis. Image Underst..