Human gait recognition based on bilinear modeling and HMM
基于双线性建模及隐马尔可夫模型的步态识别算法

Motivated by bi-factor-invariant human gait recognition problem,a new gait recognition algorithm was proposed in which two factors,generically called "style" and "content" were analyzed and manipulated.First,image sequences were clustered into a fixed number of content with fixed dynamics HMM-EM algorithm.Then the observation data were generated according to an asymmetric bilinear model.After that,SVD and NN were used to classify new sequences characterized by a different style label.Body width between vertical line through centroid and outer contour was used as the feature.Test on the CASIA datasets shows the proposed method's advantage in increasing the recognition rate and adapting to new styles or content.Some other facts affecting ID identification were also discussed.