Abstract
Humans are experts at recognizing intent and emotion from other people’s body movements; however, the underlying mechanisms are poorly understood. Here, we computed quantitative features of body posture and kinematics and acquired behavioural ratings of these feature descriptors to investigate their role in affective whole-body movement perception. Representational similarity analyses and classification regression trees were used to investigate the relation of emotional categories to both the computed features and behavioural ratings. Overall, postural rather than kinematic features discriminated better between emotional movements for the computed as well as for the behavioural features. In particular, limb angles and symmetry appeared to be the most relevant ones. This was observed independently of whether or not the time-related information was preserved in the computed features. Interestingly, the behavioural ratings showed a clearer distinction between affective movements than the computed counterparts. Finally, the perceived directionality of the movement (i.e. towards or away from the observer) was found to be critical for the recognition of fear and anger.
Highlights
Humans are experts at recognizing intent and emotion from other people’s body movements; the underlying mechanisms are poorly understood
Neither the body features driving the perception of the emotional content nor the features that play a prominent role in our conscious feelings have been systematically investigated
A better understanding of the core features of nonverbal communication will have a crucial impact on the theories of social interaction, and will directly benefit many areas of society, especially health care, where this knowledge could be useful in the treatment of affective communication disorders
Summary
Humans are experts at recognizing intent and emotion from other people’s body movements; the underlying mechanisms are poorly understood. In contrast to the use of qualitative descriptions and categories, computer scientists are increasingly interested in modelling the properties of body postures and movements[6,7,8,9,10,11] This requires a detailed analysis of the complex information conveyed by body movements: kinematic (e.g. velocity), dynamics (e.g. mass and force) and posture/ form information and its changes over time[12]. More naturalistic dynamic stimuli are needed to gain insight on how low-level visual body attributes contribute to the perception of specific affective states Their use, comes with difficulties since the configuration of whole-body expressions presents a high dimensionality, and its overall shape varies strongly during movement[10,18]
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