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Current face recognition methods are mainly based on face database. Face recognition task in natural environment demands face recognition algorithm has the rejection capability for the face samples out of face database, but existing methods lack this rejection ability for non-target samples. In this paper, a new hierarchical face recognition algorithm is proposed which can reject non-database test...
Face recognition has received significant attention in the last decades for many potential applications. Recently, the scale invariant feature transform (SIFT) becomes an interesting technique for the task of object recognition. This paper investigated the application of the SIFT approach to the face recognition and proposed a new method based on SIFT and support vector machine (SVM) for the face...
As a large-scale database of hundreds of thousands of face images collected from the Internet and digital cameras becomes available, how to utilize it to train a well-performed face detector is a quite challenging problem. In this paper, we propose a method to resample a representative training set from a collected large-scale database to train a robust human face detector. First, in a high-dimensional...
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