Title :
Symmetry description and face recognition using face symmetry based on local binary pattern feature
Author :
Wang Ya-Nan ; Su Jian-Bo
Author_Institution :
Dept. of Autom., Shanghai Jiaotong Univ., Shanghai, China
Abstract :
Considering the face image is approximate symmetry, we proposed a measurement factor to quantify the symmetrical characteristic of face images. Firstly we transform the face image into even-odd face images using parity decomposition method. LBP features extracted in even images to construct training sets. Then we apply Adaboost training algorithm to structure a strong classifier. Experiment proved that this method can overcome environment disturbance, and effectively improve the recognition rate.
Keywords :
face recognition; feature extraction; image classification; learning (artificial intelligence); matrix decomposition; Adaboost training algorithm; LBP feature extraction; classifier; environment disturbance; even-odd face images; face images symmetrical characteristic; face recognition; face symmetry; local binary pattern feature; measurement factor; parity decomposition method; recognition rate; symmetry description; training sets; Boosting; Electronic mail; Face; Face recognition; Feature extraction; Silicon; Training; Adaboost; Face Recognition; Face Symmetry; Local Binary Pattern;
Conference_Titel :
Control Conference (CCC), 2013 32nd Chinese
Conference_Location :
Xi´an
