Automatic extraction and description of human gait models for recognition purposes
Computer Vision and Image Understanding
Stride and Cadence as a Biometric in Automatic Person Identification and Verification
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Gait recognition using linear time normalization
Pattern Recognition
Human Recognition at a Distance in Video
Human Recognition at a Distance in Video
Fusion of static and dynamic body biometrics for gait recognition
IEEE Transactions on Circuits and Systems for Video Technology
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We concentrate on recognizing persons according to the way they walk. Our approach considers a human movement as a set of trajectories of hips, knees, and feet captured as the person walks. The trajectories are used for the extraction of viewpoint invariant planar signals that express how a distance between a pair of specific points on the human body changes in time. We solely focus on analysis and normalization of extracted signals to simplify their similarity comparison, without presenting any specific gait recognition method. In particular, we propose a novel method for automatic determination of walk cycles within extracted signals and evaluate its importance on a real-life human motion database.