论文信息 - Approach to Human Activity Multi-scale Analysis and Recognition Based on Multi-layer Dynamic Bayesian Network: Approach to Human Activity Multi-scale Analysis and Recognition Based on Multi-layer Dynamic Bayesian Network - 字舞流文

Approach to Human Activity Multi-scale Analysis and Recognition Based on Multi-layer Dynamic Bayesian Network: Approach to Human Activity Multi-scale Analysis and Recognition Based on Multi-layer Dynamic Bayesian Network

Feng Chen | Wen-Li Xu | You-Tian Du

[1] Xiaohui Liu,et al. Multi-agent activity recognition using observation decomposedhidden Markov models , 2006, Image Vis. Comput..

[2] James W. Davis,et al. The Recognition of Human Movement Using Temporal Templates , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[3] Chiu-yu Tseng,et al. Isolated-utterance speech recognition using hidden Markov models with bounded state durations , 1991, IEEE Trans. Signal Process..

[4] Michael I. Jordan,et al. Factorial Hidden Markov Models , 1995, Machine Learning.

[5] Yoram Singer,et al. The Hierarchical Hidden Markov Model: Analysis and Applications , 1998, Machine Learning.

[6] Aaron F. Bobick,et al. Recognition of Visual Activities and Interactions by Stochastic Parsing , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[7] Stephen E. Levinson,et al. Continuously variable duration hidden Markov models for automatic speech recognition , 1986 .