The visual analysis of human movement: a survey
Computer Vision and Image Understanding
Human motion analysis: a review
Computer Vision and Image Understanding
Gait-Based Recognition of Humans Using Continuous HMMs
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Silhouette-Based Human Identification from Body Shape and Gait
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Motion-Based Recognition of People in EigenGait Space
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Identification of humans using gait
IEEE Transactions on Image Processing
Hand gesture recognition based on dynamic Bayesian network framework
Pattern Recognition
| Hi-index | 0.00 |
Recently human gait has been considered as a useful biometric supporting high performance human identification systems. We propose a view-based pedestrian identification method using the dynamic silhouettes of a human body modeled with the hidden Markov model (HMM). Two types of gait models have been developed both with a cyclic architecture: one is a discrete HMM method using a self-organizing map-based VQ codebook and the other is a continuous HMM method using feature vectors transformed into a PCA space. Experimental results showed a consistent performance trend over a range of model’s parameters and the recognition rate up to 88.1%. Compared with other methods, the proposed models and techniques are believed to have a sufficient potential for a successful application to gait recognition.