Human behavior analysis for human-robot interaction in indoor environments

Intelligent service robots should understand the needs of human beings, recognize their environment, and perform reliable tasks. To enable robots to achieve these activities, we need to understand the behavior patterns of human beings first. In recent research, there were some attempts to recognize human intentions through multimodal information systems. In this paper, human behaviors in indoor daily life were analyzed to obtain a pattern. We also suggested the use of the semantic segmentation method for the prediction of succeeding actions and for a better understanding of the robots' intentions. Finally, the validity of the suggested method was evaluated through real behavior data.