Distributed Face Recognition via Consensus on SE(3)

Abstract : We consider the problem of distributed face recognition in a calibrated camera sensor network. We assume that each camera is given a small and possibly different training set of face images taken under varying viewpoint, expression, and illumination conditions. Each camera can estimate the pose and identity of a new face using classical techniques such as Eigenfaces or Tensorfaces combined with a simple classifier. However, the pose estimates obtained by a single camera could be very poor, due to limited computational resources, impoverished training sets, etc., which could lead to poor recognition results. Our key contribution is to propose a distributed face recognition algorithm in which neighboring cameras share their individual estimates of the pose in order to achieve a “consensus” on the face pose. For this purpose, we use a provably convergent distributed consensus algorithm on SE(3) that estimates the global Karcher mean of the face pose in a distributed fashion. Experiments on the Weizmann database show that our algorithm effectively improves the local pose estimates, and achieves the performance of centralized face recognition algorithms using only local processing.
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Communication dans un congrès
The 8th Workshop on Omnidirectional Vision, Camera Networks and Non-classical Cameras - OMNIVIS, Oct 2008, Marseille, France. 2008
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Roberto Tron, René Vidal. Distributed Face Recognition via Consensus on SE(3). The 8th Workshop on Omnidirectional Vision, Camera Networks and Non-classical Cameras - OMNIVIS, Oct 2008, Marseille, France. 2008. 〈inria-00325387〉

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