A Similar Interaction Model for Group Activity Recognition in Still Images.

This paper addresses the group activity recognition in the still image. We formulate an alternative discriminant contextual model on feature level. On the one hand, it mines the person-joint-context feature model, which describes the interaction of a focal person and its surrounding context. In the meanwhile, the surrounding context is featured with the relative pose, relative location and the scene background. On the other hand, a similar interaction model is formed to learn the interactive correlation between a focal person and its surrounding context. An optimization criterion is proposed to learn the similar interaction model. We show that the optimization problem can be optimized efficiently. Our experimental results show that the proposed model outperforms related works, even though temporal information is not available.