Facial Expression Detection Techniquesbased on Viola and Jones Algorithm and Principal Component Analysis
Facial Expression Detection Techniques: based on Viola and Jones Algorithm and Principal Component Analysis
Facial expression is a prominent posture beneath the skin of the face. They are the way of communication in humans which convey many things non-verbally. During the past years face recognition has received significant attention as one of the most important applications of image understanding and analysis. Many algorithms have been implemented on different static and non-static conditions. Static conditions include static and uniform background, identical poses, similar illumination, neutral frontal face. Non static conditions include position, partial occlusion orientation, varying lightening conditions and facial hair which make recognition process a complex problem. All these factors influence face recognition process. The main stages for face recognition include face detection, feature representation and classifications. Researchers have described distinct approaches for face recognition. In this work we present a glimpse of face detection techniques, methods used, their performance & their limitations and proposed a new technique for Face Detection based on Viola and Jones algorithm and principal component analysis. At the end we have shown simulation results for the proposed technique and established that proposed technique is performing better than the existing one. The proposed system is implemented in MATLAB version 188.8.131.52.739 (R2012a).
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