Keeping smart, omnidirectional eyes on you [adaptive panoramic stereovision]

Zhigang Zhu
Deepak R. Karuppiah, University of Massachusetts - Amherst
Edward Riseman, University of Massachusetts - Amherst
Allen Hanson, University of Massachusetts - Amherst

Abstract

An adaptive panoramic stereo approach for two cooperative mobile platform is presented. There are four key features in the approach: 1) omnidirectional stereovision with an appropriate vertical FOV, and a simple camera calibration method; 2) cooperative mobile platforms for mutual dynamic calibration and best view planning; 3) 3D matching after meaningful object (human subject) extraction; and 4) real-time performance. The integration of omnidirectional vision with mutual awareness and dynamic calibration strategies allows intelligent cooperation between visual agents. This provides an effective way to solve the problems of limited resources, view planning, occlusion, and motion detection of movable robotic platforms. Experiments have shown that this approach is quite promising.