Facial expression analysis using 2D and 3D features

Powar, N.U.,Foytik, J.D.,Asari, V.K.,Vajaria, H.

Aerospace and Electronics Conference（2011）

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摘要

Psychological research for the recognition of emotions from facial expressions have evolved over the years. Recent technological advances in imaging, computing, computer vision, and pattern recognition have paved the way for automating facial expression recognition. The proposed approach in this paper presents our initial expression classification research using Hidden Markov Models (HMM) on 2D texture facial data. A surface curvature based feature extraction technique involving geometric facial data from unique 3D sensors is also being investigated. It is expected that the proposed methodologies could provide significant improvements in facial expression and emotion recognition performance.

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关键词

emotion recognition,face recognition,hidden Markov models,image sensors,image texture,pattern recognition,2D features,2D texture facial data,3D features,3D sensors,HMM,Hidden Markov models,computer vision,emotion recognition,extraction technique,facial expression analysis,geometric facial data,initial expression classification,pattern recognition,psychological research,surface curvature,3D,Automatic FER,Emotion Recognition,Hidden Markov Models,Realtime,

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