A New Approach for Facial Expression Recognition Based on Burial Markov Model
Fuzzy Systems and Knowledge Discovery, 2008. FSKD '08. Fifth International Conference（2008）
摘要
To overcome the disadvantage of classical recognition model which cannot perform enough well when there are some noises or lost frames in expression image sequencers, a novel model called Burial Markov Model is applied in facial expression recognition based on video image sequences. Compared with Hidden Markov model, Buried Markov Model (BMM), as an improved technology of HMM, adds the specific cross-observation dependencies between observation elements in order to increase both accuracy and discriminability. Theoretical justifications and experimental results show that facial expression recognition of video frames based on BMM can get high recognition rate and has strong robustness.
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关键词
expression image sequencers,facial expression recognition,novel model,hidden markov model,video image sequence,burial markov model,new approach,markov model,classical recognition model,video frame,high recognition rate,entropy,face recognition,image recognition,training data,hidden markov models,markov processes,approximation algorithms,mutual information
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