A Machine Learning Algorithm of Human-Computer-Interface Application-An AdaRank Model Approach to Facial Expression Recognition
A completely automatic facial expression recognition system is presented in this paper,which consists of three main procedures.The tint is based on skin color blocks and geometrical properties applied to eliminate the skin color regions that do not belong to the face in the HSV color space.Than we find proper ranges of eyes,mouth,and eyebrows according to the positions of pupils and center of a mouth.Subsequently,we perform both the edge detection and binarization operations on the above ranged images to obtain 16 landmarks.After manipulating these landmarks,16 characteristic distances are the facial feature produced to represent a kind of expressions.Finally,we subtract the 16 characteristic distances of a neutral face from the 16 characteristic distances of a certain expression to acquire its 16displacement values fed to a classifier with an incrementallearning scheme,which can identify six kinds of expressions:joy,anger,surprise,fear,sadness,and neutral we choose the AdaRank model aa the core technique to implement our strong facial expression classifier.Our model,referred to as AdaRank,repeatedly constructs classifiers on the bash of re-weighted training data and finally linearly combines the classiflers for making ranking predictions.Through conducting many experiments,the statistics of performance reveals that the accuracy rate of our facial expression recognition system reaches more than 95%.
facial expression recognition landmarks facial feature,AdaRank
Chang-Yi Kao Chin-Shyurng Fahn
Institute for Information Industry Taipei,Taiwan 10607,Republic of China National Taiwan University of Science and Technology Taipei,Taiwan 10607,Republic of China
国际会议
杭州
英文
160-163
2013-03-22（万方平台首次上网日期，不代表论文的发表时间）