Recognizing social interactions, e.g. two people shaking hands, is important for obtaining information about other people and the surrounding social environment. Despite the visual complexity of social interactions, humans have often little difficulties to visually recognize social interactions. What is the visual representation of social interactions and the bodily visual cues that promote this remarkable human ability? Viewpoint dependent representations are considered to be at the heart of the visual recognition of many visual stimuli including objects (Bülthoff & Edelman, 1992), and biological motion patterns (Verfaillie, 1993). Here we addressed the question whether complex social actions acted out between pairs of people, e.g. hugging, are also represented in a similar manner. To this end, we created 3-D models from motion captured actions acted out by two people, e.g. hugging. These 3-D models allowed to present the same action from different viewpoints. Participants task was to discriminate a target action from distractor actions using a one-interval-forced-choice (1IFC) task. We measured participants' recognition performance in terms of reaction times (RT) and d-prime (d'). For each tested action we found one view that lead to superior recognition performance compared to other views. This finding demonstrates view-dependent effects of visual recognition, which are in line with the idea of a view dependent representations of social interactions. Subsequently, we examined the degree to which velocities of joints are able to predict the recognition performance of social interactions in order to determine candidate visual cues underlying the recognition of social interactions. We found that the velocities of the right arm, lower left leg, and both feet correlated with recognition performance.