Unsupervised Clustering for Google Searches of Celebrity Images

Abstract

How do we identify images of the same person in photo albums? How can we find images of a particular celebrity using web image search engines? These types of tasks require solving numerous challenging issues in computer vision including: detecting whether an image contains a face, maintaining robustness to lighting, pose, occlusion, scale, and image quality, and using appropriate distance metrics to identify and compare different faces. In this paper we present a complete system which yields good performance on challenging tasks involving face recognition including image retrieval, unsupervised clustering of faces, and increasing precision of 'Google Image' searches. All tasks use highly variable real data obtained from raw image searches on the web.

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