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Learning Actions from the Identity in the Web
2014
Journal of Computer and Communications
This paper proposes an efficient and simple method for identity recognition in uncontrolled videos. The idea is to use images collected from the web to learn representations of actions related with identity, use this knowledge to automatically annotate identity in videos. Our approach is unsupervised where it can identify the identity of human in the video like YouTube directly through the knowledge of his actions. Its benefits are two-fold: 1) we can improve retrieval of identity images, and
doi:10.4236/jcc.2014.29008
fatcat:xoitz4jidje57fajvr2unnbjjy