An Efficient Approach to Facial Feature Detection for Expression Recognition

An Intelligent Biometrics systems aims at localizing and detecting human faces from supplied images so that further recognition of persons and their facial expression recognition will be easy. Based on facial expression; one can predict about intension of person Method includes supplying a face image as an input and facial features like eyebrow, eyes, nose, and mouth are given as output after detecting face. These facial features are then used as feature vectors for recognizing facial expression. This paper presents an efficient detection of face and facial features from an image so that the detected face and features can be used for facial expression recognition. Images obtained from Sony make digital camera (resolution 7.1 Mega pixel) are considered for our work. Also some images from Standard database like JAFFE and Cohn-Kanade are used in our experiments. Method used includes combination of skin detection algorithms such as modified RGB, YCbCr and HSV for colored images and gives better results. Experimental result shows that the algorithm is good to detect and localize human face and to detect facial features in an image with better accuracy.

[1]  S. P. Khandait,et al.  Hybrid Skin Detection Algorithm for Face localization in facial Expression Recognition , 2009, 2009 IEEE International Advance Computing Conference.

[2]  Nur Izura Udzir,et al.  Extract of Facial Feature Point , 2009 .

[3]  Takeo Kanade,et al.  Evaluation of Gabor-wavelet-based facial action unit recognition in image sequences of increasing complexity , 2002, Proceedings of Fifth IEEE International Conference on Automatic Face Gesture Recognition.

[4]  Michael J. Lyons,et al.  Coding facial expressions with Gabor wavelets , 1998, Proceedings Third IEEE International Conference on Automatic Face and Gesture Recognition.

[5]  Amitabha Mukerjee,et al.  ROBUST FACIAL EXPRESSION RECOGNITION USING SPATIALLY LOCALIZED GEOMETRIC MODEL , 2004 .

[6]  L YuilleAlan,et al.  Feature extraction from faces using deformable templates , 1992 .

[7]  Takeo Kanade,et al.  Computer recognition of human faces , 1980 .

[8]  Takeo Kanade,et al.  Comprehensive database for facial expression analysis , 2000, Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580).