Methodological Issues of Annotating Vision Sensor Data using Subjects' Own Judgement of Comfort in a Robot Human Following Experiment

Abstract

When determining subject preferences for human-robot interaction, an important issue is the interpretation of the subjects' responses during the trials. Employing a non-intrusive approach, this paper discusses the methodological issues for annotating vision data by allowing the subjects to indicate their comfort using a handheld comfort level device during the trials. In previous research, the analysis of collected comfort and vision data was made difficult due to problems concerning the manual synchronization of different modalities. In the current paper, we overcome this issue by real-time integration of the subject's feedback on subjective comfort into the video stream. The implications for more efficient analysis of human-robot interaction data, as well as possible future developments of this approach are discussed