We present a novel approach for jointly estimating targets' head, body orientations and conversational groups called F-formations from a distant social scene (e.g., a cocktail party captured by surveillance cameras). Differing from related works that have (i) coupled head and body pose learning by exploiting the limited range of orientations that the two can jointly take, or (ii) determined F-formations based on the mutual head (but not body) orientations of interactors, we present a unified framework to jointly infer both (i) and (ii). Apart from exploiting spatial and orientation relationships, we also integrate cues pertaining to temporal consistency and occlusions, which are beneficial while handling low-resolution data under surveillance settings. Efficacy of the joint inference framework reflects via increased head, body pose and F-formation estimation accuracy over the state-of-the-art, as confirmed by extensive experiments on two social datasets.
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