PLAViMoP database: A new continuously assessed and collaborative 3D point-light display dataset.

It was more than 45 years ago that Gunnar Johansson invented the point-light display technique. This showed for the first time that kinematics is crucial for action recognition, and that humans are very sensitive to their conspecifics' movements. As a result, many of today's researchers use point-light displays to better understand the mechanisms behind this recognition ability. In this paper, we propose PLAViMoP, a new database of 3D point-light displays representing everyday human actions (global and fine-motor control movements), sports movements, facial expressions, interactions, and robotic movements. Access to the database is free, at https://plavimop.prd.fr/en/motions . Moreover, it incorporates a search engine to facilitate action retrieval. In this paper, we describe the construction, functioning, and assessment of the PLAViMoP database. Each sequence was analyzed according to four parameters: type of movement, movement label, sex of the actor, and age of the actor. We provide both the mean scores for each assessment of each point-light display, and the comparisons between the different categories of sequences. Our results are discussed in the light of the literature and the suitability of our stimuli for research and applications.

Perception of robotic actions and the influence of gender.

In our society interaction with robots is becoming more and more frequent since robots are not only used in the industry, but increasingly often in assistance and in health system. Perception of robots and their movements is crucial for their acceptance. Here we shortly review basic mechanisms of perception of actions, and then of perception of robotic and human movements. The literature demonstrates that there are commonalities, but also differences in the perception of human and robotic movements. Especially interesting are biologic gender differences in the perception of robotic movements. The results show that males seem to be more sensitive to the differences between robotic and anthropomorphic movements, whereas females seem not to perceive such differences. However, females transfer more anthropomorphic features to robotic movements. While looking at the brain activation during perception of humanoid and robotic movements in different genders one can conclude that different strategies are used; female seem to analyse robotic movements online, while male seem to use previous knowledge from interaction with robots. Further research is needed to specify more such gender differences.