Adaptive Panoramic Stereovision for Human Tracking and Localization with Cooperative Robots

Abstract

An adaptive panoramic stereo vision approach for localizing 3D moving objects has been developed in the Department of Computer Science at the University of Massachusetts at Amherst. This research focuses on cooperative robots involving cameras (residing on different mobile platforms) that can be dynamically composed into a virtual stereo vision system with flexible baseline in order to detect, track, and localize moving human subjects in an unknown indoor environment. This work was carried out under the support of the DARPA ITO Software for Distributed Robotics (SDR) and Autonomous Mobile Robot Software (MARS). This research project is relevant to both civil and military applications with distributed stationary and mobile perceptual agents. Applications are widespread, such as video surveillance and monitoring, security, crowd control, intelligent rooms and office, etc. For example, we are currently looking into applications in metropolitan scenarios such as New York City for solving problems of finding and protecting people in emergency circumstances, for example, during a terrorist attack or a fire in an office building.