In this paper we propose a new face recognition approach based on DAISY, a dense computed SIFT-like descriptor. Our algorithm is designed to be fast for dense computation, and useful for re-identification as it is able to distinguish pairs of images as belonging to the same subject or not. The descriptors are computed densely and matched with a new strategy that represents an efficient trade off between accuracy and computational load; afterwards a Support Vector Machine is used to classify the output of the matching to recognize if the pair of images belongs to the same person. An analysis of performance will be conducted on two different databases in order to compare our results with the already existing ones. We show that better performance than SIFT techniques can be achieved using our algorithm.
Face recognition with DAISY descriptors
MM&SEC 2010, ACM SIGMM Multimedia and Security Workshop, September 9-10, Rome, Italy
© ACM, 2010. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in MM&SEC 2010, ACM SIGMM Multimedia and Security Workshop, September 9-10, Rome, Italy http://dx.doi.org/10.1145/1854229.1854249
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