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Understanding social interactions (such as 'hug' or 'fight') is a basic andimportant capacity of the human visual system, but a challenging and still openproblem for modeling. In this work we study visual recognition of socialinteractions, based on small but recognizable local regions. The approach isbased on two novel key components: (i) A given social interaction can berecognized reliably from reduced images (called 'minimal images'). (ii) Therecognition of a social interaction depends on identifying components andrelations within the minimal image (termed 'interpretation'). We showpsychophysics data for minimal images and modeling results for theirinterpretation. We discuss the integration of minimal configurations inrecognizing social interactions in a detailed, high-resolution image.

A model for interpreting social interactions in local image regions