A New Approach for Facial Expression Recognition Based on Burial Markov Model
Keyang Cheng, Chen Yabi, Yongzhao Zhan · 2008
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.