Posture and Activity Silhouettes for Self-Reporting, Interruption Management, and Attentive Interfaces

摘要

In this paper we present a novel system for monitoring a computer user's posture and activities in front of the computer (e.g., reading, speaking on the phone, etc.) for self-reporting. In our system, a camera and a microphone are placed in front of a computer work area (e.g., on top of the computer screen). The system can be used as a component in an attentive interface, or for giving the user real time feedback on the goodness of his current posture, and generating summaries of postures and activities over a specified period of time (e.g., hours, days, months, etc.). All elements of the system are highly customizable: the user decides what "good" postures are, what alarms and interruptions are triggered, if any, and what activity and posture summaries are generated. We present novel algorithms for posture measurement (using geometric features of the user's silhouette), and activity classification (using machine learning). Finally, we present experiments that show the feasibility of our approach.