Moving object recognition in eigenspace representation: gait analysis and lip reading
Pattern Recognition Letters
Mapping a manifold of perceptual observations
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
A Multi-view Method for Gait Recognition Using Static Body Parameters
AVBPA '01 Proceedings of the Third International Conference on Audio- and Video-Based Biometric Person Authentication
Individual recognition from periodic activity using hidden Markov models
HUMO '00 Proceedings of the Workshop on Human Motion (HUMO'00)
Automatic extraction and description of human gait models for recognition purposes
Computer Vision and Image Understanding
Automatic gait recognition by symmetry analysis
Pattern Recognition Letters - Special issue: Audio- and video-based biometric person authentication (AVBPA 2001)
Baseline Results for the Challenge Problem of Human ID Using Gait Analysis
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Gait Analysis for Recognition and Classification
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
A Theory of Networks for Approximation and Learning
A Theory of Networks for Approximation and Learning
Separating Style and Content with Bilinear Models
Neural Computation
Action synopsis: pose selection and illustration
ACM SIGGRAPH 2005 Papers
Improved Gait Recognition by Gait Dynamics Normalization
IEEE Transactions on Pattern Analysis and Machine Intelligence
Human gait recognition at sagittal plane
Image and Vision Computing
IEICE - Transactions on Information and Systems
Hybrid Dynamical Models of Human Motion for the Recognition of Human Gaits
International Journal of Computer Vision
Bilinear Models for Spatio-Temporal Point Distribution Analysis
International Journal of Computer Vision
Towards scalable view-invariant gait recognition: multilinear analysis for gait
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
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Human Identification using gait is a challenging computer vision task due to the dynamic motion of gait and the existence of various sources of variations such as viewpoint, walking surface, clothing, etc. In this paper we propose a gait recognition algorithm based on bilinear decomposition of gait data into time-invariant gait-style and timedependent gait-content factors. We developed a generative model by embedding gait sequences into a unit circle and learning nonlinear mapping which facilitates synthesis of temporally-aligned gait sequences. Given such synthesized gait data, bilinear model is used to separate invariant gait style which is used for recognition. We also show that the recognition can be generalized to new situations by adapting the gait-content factor to the new condition and therefore obtain corrected gait-styles for recognition.