PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Who's Doing What: Joint Modeling of Names and Verbs for Simultaneous Face and Pose Annotation
Luo Jie, Barbara Caputo and Vittorio Ferrari
In: NIPS 2009, Dec 2009, Vancouver.

Abstract

Given a corpus of news items consisting of images accompanied by text captions, we want to find out ``who's doing what'', i.e. associate names and action verbs in the captions to the face and body pose of the persons in the images. We present a joint model for simultaneously solving the image-caption correspondences and learning visual appearance models for the face and pose classes occurring in the corpus. These models can then be used to recognize people and actions in novel images without captions. We demonstrate experimentally that our joint `face and pose' model solves the correspondence problem better than earlier models covering only the face, and that it can perform recognition of new uncaptioned images.

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EPrint Type:Conference or Workshop Item (Poster)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
Learning/Statistics & Optimisation
ID Code:5736
Deposited By:Vittorio Ferrari
Deposited On:08 March 2010