3D Human Sensing, Action and Emotion Recognition in Robot Assisted下载

We introduce new, fine-grained action and emotion recognition tasks defined on non-staged videos, recorded during robot-assisted therapy sessions of children with autism. The tasks present several challenges: a large dataset with long videos, a large number of highly vari- able actions, children that are only partially visible, have different ages and may show unpredictable behaviour, as well as non-standard camera viewpoints. We investigate how state-of-the-art 3d human pose reconstruction methods perform on the newly introduced tasks and propose exten- sions to adapt them to deal with these challenges. We also analyze multiple approaches in action and emotion recogni- tion from 3d human pose data, establish several baselines, and discuss results and their implications in the context of child-robot interaction.