Commentary on "Experimental Analysis of Face Recognition on from Still Image to Video Image"

Evaluation of face recognition performance under varying illumination, poses, and image degradation due to sensor characteristics has been studied in depth for static images. This paper uses static and video images when evaluating a face recognition algorithm based on ¿Adaptive Principal Components Analysis¿ (APCA). The results show that the same challenges that happen in static images apply to video, and that when multiple images are available the algorithms perform better (e.g. using, mean frames for face recognition).

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