Incremental Learning for Video-Based Gait Recognition With LBP Flow
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James J. Little | Yunhong Wang | Zhaoxiang Zhang | De Zhang | Maodi Hu | J. Little | Yunhong Wang | De Zhang | Zhaoxiang Zhang | Maodi Hu
[1] Rama Chellappa,et al. Gait Analysis for Human Identification , 2003, AVBPA.
[2] M. Hildebrand. Vertebrate Locomotion: An IntroductionHow does an animal's body move itself along? , 1989 .
[3] Jitendra Malik,et al. Recognizing action at a distance , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.
[4] Sudeep Sarkar,et al. Effect of silhouette quality on hard problems in gait recognition , 2005, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[5] Eamonn J. Keogh,et al. Three Myths about Dynamic Time Warping Data Mining , 2005, SDM.
[6] Jeff A. Bilmes,et al. A gentle tutorial of the em algorithm and its application to parameter estimation for Gaussian mixture and hidden Markov models , 1998 .
[7] Jitendra Malik,et al. Large displacement optical flow , 2009, CVPR.
[8] Sudeep Sarkar,et al. Studies on silhouette quality and gait recognition , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..
[9] Jitendra Malik,et al. Large Displacement Optical Flow: Descriptor Matching in Variational Motion Estimation , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[10] N. L. Johnson,et al. Multivariate Analysis , 1958, Nature.
[11] Rama Chellappa,et al. Ieee Transactions on Pattern Analysis and Machine Intelligence 1 Matching Shape Sequences in Video with Applications in Human Movement Analysis. Ieee Transactions on Pattern Analysis and Machine Intelligence 2 , 2022 .
[12] Shuicheng Yan,et al. An HOG-LBP human detector with partial occlusion handling , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[13] Takao Miura,et al. Data Stream Prediction Using Incremental Hidden Markov Models , 2009, DaWaK.
[14] Cordelia Schmid,et al. Human Detection Using Oriented Histograms of Flow and Appearance , 2006, ECCV.
[15] Kelson Rômulo Teixeira Aires,et al. Optical flow using color information: preliminary results , 2008, SAC '08.
[16] Pietro Perona,et al. Continuous dynamic time warping for translation-invariant curve alignment with applications to signature verification , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.
[17] M. Nixon,et al. Human gait recognition in canonical space using temporal templates , 1999 .
[18] Lawrence R. Rabiner,et al. A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.
[19] John B. Moore,et al. On-line estimation of hidden Markov model parameters based on the Kullback-Leibler information measure , 1993, IEEE Trans. Signal Process..
[20] Ming-Hsuan Yang,et al. Incremental Learning for Robust Visual Tracking , 2008, International Journal of Computer Vision.
[21] A. B. Drought,et al. WALKING PATTERNS OF NORMAL MEN. , 1964, The Journal of bone and joint surgery. American volume.
[22] ChellappaRama,et al. Matching Shape Sequences in Video with Applications in Human Movement Analysis , 2005 .
[23] Branko Ristic,et al. Beyond the Kalman Filter: Particle Filters for Tracking Applications , 2004 .
[24] Shaogang Gong,et al. Gait Representation Using Flow Fields , 2009, BMVC.
[25] Sudeep Sarkar,et al. The humanID gait challenge problem: data sets, performance, and analysis , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[26] Aude Billard,et al. Incremental learning of gestures by imitation in a humanoid robot , 2007, 2007 2nd ACM/IEEE International Conference on Human-Robot Interaction (HRI).
[27] Oded Ghitza,et al. Auditory nerve representation as a front-end for speech recognition in a noisy environment , 1986 .
[28] Tieniu Tan,et al. Silhouette Analysis-Based Gait Recognition for Human Identification , 2003, IEEE Trans. Pattern Anal. Mach. Intell..
[29] Thomas Brox,et al. Universität Des Saarlandes Fachrichtung 6.1 – Mathematik Highly Accurate Optic Flow Computation with Theoretically Justified Warping Highly Accurate Optic Flow Computation with Theoretically Justified Warping , 2022 .
[30] Waseem Ahmad. Incremental Learning of Gaussian Mixture Models , 2006 .
[31] Chung-Lin Huang,et al. Gait Analysis For Human Identification Through Manifold Learning and HMM , 2007, 2007 IEEE Workshop on Motion and Video Computing (WMVC'07).
[32] M P Murray,et al. COMPARISON OF FREE AND FAST SPEED WALKING PATTERNS OF NORMAL MEN , 1966, American journal of physical medicine.
[33] R. Vidal,et al. Histograms of oriented optical flow and Binet-Cauchy kernels on nonlinear dynamical systems for the recognition of human actions , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[34] Thomas Brox,et al. High Accuracy Optical Flow Estimation Based on a Theory for Warping , 2004, ECCV.
[35] John B. Moore,et al. Discrete-time fixed-lag smoothing algorithms , 1973 .
[36] H. Sung. Gaussian Mixture Regression and Classification , 2004 .
[37] Joachim M. Buhmann,et al. Topology Free Hidden Markov Models: Application to Background Modeling , 2001, ICCV.
[38] Tieniu Tan,et al. A Study on Gait-Based Gender Classification , 2009, IEEE Transactions on Image Processing.
[39] Euntai Kim,et al. Gait recognition using multi-bipolarized contour vector , 2009 .
[40] Sylvain Calino,et al. Robot programming by demonstration : a probabilistic approach , 2009 .
[41] 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.
[42] Z. Liu,et al. Simplest representation yet for gait recognition: averaged silhouette , 2004, ICPR 2004.
[43] Sudeep Sarkar,et al. Improved gait recognition by gait dynamics normalization , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[44] Dariu Gavrila,et al. Multi-cue pedestrian classification with partial occlusion handling , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[45] Euntai Kim,et al. A noise robust gait representation: Motion energy image , 2009 .
[46] M. P. Murray. Gait as a total pattern of movement. , 1967, American journal of physical medicine.
[47] Susan M. Bridges,et al. Incremental Estimation of Discrete Hidden Markov Models Based on a New Backward Procedure , 2005, AAAI.
[48] Matti Pietikäinen,et al. A comparative study of texture measures with classification based on featured distributions , 1996, Pattern Recognit..
[49] J. Little,et al. Recognizing People by Their Gait: The Shape of Motion , 1998 .
[50] 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).
[51] Murray Mp,et al. Gait as a total pattern of movement. , 1967 .
[52] Kinh Tieu,et al. Learning pedestrian models for silhouette refinement , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.
[53] Euntai Kim,et al. Regularized eigenspace-based gait recogntion system for human identification , 2011, 2011 6th IEEE Conference on Industrial Electronics and Applications.
[54] Matti Pietikäinen,et al. Face Description with Local Binary Patterns: Application to Face Recognition , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[55] Bill Triggs,et al. Histograms of oriented gradients for human detection , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).