Face quality assessment for face verification in video

Performance of biometric systems depends on quality of acquired biometric samples. Low sample quality is the main reason for matching errors in biometric systems and may be the principal weakness of some implementations. Therefore, when a biometric system obtains a sequence of person images from a surveillance camera, the quality of the different face images has to be evaluated before performing any analysis on the face of a person. In this paper, we propose an approach for face image quality assessment, which is based on four facial features including facial symmetry, sharpness, quality of illumination and the image resolution. To produce overall face quality score we perform weighted fusion of facial features with automatically tuned weights. Experimental evaluation of the proposed method has demonstrated its high accuracy and efficiency.

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