Title :
A New Approach for Facial Expression Recognition Based on Burial Markov Model
Author :
Cheng, Keyang ; Chen, Yabi ; Zhan, Yongzhao
Author_Institution :
Sch. of Comput. Sci., Jiangsu Univ., Zhenjiang
Abstract :
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.
Keywords :
Markov processes; face recognition; image sequences; video signal processing; burial Markov model; facial expression recognition; video image sequence; Computer science; Context modeling; Face recognition; Facial animation; Fuzzy systems; Hidden Markov models; Image recognition; Independent component analysis; Mutual information; Principal component analysis; Buried Markov Model; Hidden Markov Model; facial expression recognition;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2008. FSKD '08. Fifth International Conference on
Conference_Location :
Jinan Shandong
Print_ISBN :
978-0-7695-3305-6
DOI :
10.1109/FSKD.2008.362