Computer Science ›› 2015, Vol. 42 ›› Issue (3): 289-295.doi: 10.11896/j.issn.1002-137X.2015.03.060

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Face Recognition with Occlusion Based on Removing Outliers Area

LI Dong-mei, XIONG Cheng-yi, GAO Zhi-rong, ZHOU Cheng and WANG Han-xin   

  • Online:2018-11-14 Published:2018-11-14

Abstract: Aiming at the issue of face recognition with partial occlusion,an improved face recognition method based on removing the outlier area was proposed 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 considerable recognition performance improvement with relatively sample computational complexity.Simulation results based on the standard extended Yale B and AR face databasesshow effectiveness of the proposed method.

Key words: Face recognition,Partial occlusion,Detection of outliers area,Image segmentation

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