Detecting, tracking and interacting with people in a public space

We have built a system that engages naive users in an audiovisual interaction with a computer in an unconstrained public space. We combine audio source localization techniques with face detection algorithms to detect and track the user throughout a large lobby. The sensors we use are an ad-hoc microphone array and a PTZ camera. To engage the user, the PTZ camera turns and points at sounds made by people passing by. From this simple pointing of a camera, the user is made aware that the system has acknowledged their presence. To further engage the user, we develop a face classification method that identifies and then greets previously seen users. The user can interact with the system through a simple hot-spot based gesture interface. To make the user interactions with the system feel natural, we utilize reconfigurable hardware, achieving a visual response time of less than 100ms. We rely heavily on machine learning methods to make our system self-calibrating and adaptive.

• Type: Conference
• Year: 2009
• Where: ICMI
• Authors: Sunsern Cheamanunkul, Evan Ettinger, Matt Jacobsen, Patrick Lai, Yoav Freund
• Keywords: Biometrics, Face Detection Algorithms, ICMI 2009, PTZ Camera, User