Quality based frame selection for video face recognition
Anantharajah, Kaneswaran, Denman, Simon, Sridharan, Sridha, Fookes, Clinton B., & Tjondronegoro, Dian W. (2012) Quality based frame selection for video face recognition. In Proceedings of 6th International Conference on Signal Processing and Communication Systems (ICSPCS'2012), IEEE Xplore, Gold Coast, Qld.
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Quality based frame selection is a crucial task in video face recognition, to both improve the recognition rate and to reduce the computational cost. In this paper we present a framework that uses a variety of cues (face symmetry, sharpness, contrast, closeness of mouth, brightness and openness of the eye) to select the highest quality facial images available in a video sequence for recognition. Normalized feature scores are fused using a neural network and frames with high quality scores are used in a Local Gabor Binary Pattern Histogram Sequence based face recognition system. Experiments on the Honda/UCSD database shows that the proposed method selects the best quality face images in the video sequence, resulting in improved recognition performance.
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