Abstract:Face clustering is an important topic in computer vision. It aims to put together facial images that belong to the same person. Spectral clustering-based algorithms are often used for accurate face clustering. However, a big occlusion matrix is usually needed to deal with the noise and sparse outlier terms, which makes the sparse coding process computationally expensive. Thus spectral clustering-based algorithms are difficult to extend to large scale datasets. In this paper, we use the image gradient… Show more
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