Face Recognition from Video Using the Generic Shape-Illumination Manifold

Abstract. In spite of over two decades of intense research, illumination and pose invariance remain prohibitively challenging aspects of face recognition for most practical applications. The objective of this work is to recognize faces using video sequences both for training and recognition input, in a realistic, unconstrained setup in which lighting, pose and user motion pattern have a wide variability and face images are of low resolution. In particular there are three areas of novelty: (i) we show how a photometric model of image formation can be combined with a statistical model of generic face appearance variation, learnt offline, to generalize in the presence of extreme illumination changes; (ii) we use the smoothness of geodesically local appearance manifold structure and a robust same-identity likelihood to achieve invariance to unseen head poses; and (iii) we introduce an accurate video sequence "reillumination" algorithm to achieve robustness to face motion patterns...

• Type: Conference
• Year: 2006
• Where: ECCV
• Authors: Ognjen Arandjelovic, Roberto Cipolla
• Keywords: Computer Vision, ECCV 2006, Extreme Illumination Changes, Face Appearance Variation, Face Recognition, Head Motion Variation, Perfect Recognition Rate