Title :
Face recognition with contiguous occlusion based on image segmentation
Author :
Zhirong Gao ; Dongmei Li ; Chengyi Xiong ; Jianhua Hou ; Huang Bo
Author_Institution :
Coll. of Comput. Sci., South-Central Univ. for Nat., Wuhan, China
Abstract :
Aiming to the issue of face recognition with partial contiguous occlusion, a new face recognition method was proposed by removing the outlier area in this paper. A mean face image is firstly obtained from train images, which is subtracted by the test face to form an error face image. Then the error face image is used to obtain the occlusion area of the test image by image segmentation technique, and the train images and test image are tailored by removing the corresponding occlusion area. Finally, face recognition is performed by linear regression classifier or sparse coding classifier. Compared to the similar works, the proposed method has considerably recognition performance improvement with relatively simple computational complexity. Simulation experimental results based on the standard AR face database show effectiveness of this proposed method.
Keywords :
computational complexity; face recognition; image classification; image coding; image segmentation; regression analysis; AR face database; computational complexity; error face image; face recognition; image segmentation; linear regression classifier; mean face image; partial contiguous occlusion; sparse coding classifier; train images; Encoding; Face; Face recognition; Image recognition; Image segmentation; Level set; Training; Face recognition; detection of outliers area; image segmentation; partial contiguous occlusion;
Conference_Titel :
Audio, Language and Image Processing (ICALIP), 2014 International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4799-3902-2
DOI :
10.1109/ICALIP.2014.7009777