Software mode changes for continuous motion tracking
IWSAS' 2000 Proceedings of the first international workshop on Self-adaptive software
Computer Vision and Image Understanding
Omni-Directional Stereoscopic Images from One Omni-Directional Camera
Journal of VLSI Signal Processing Systems
Camera Models and Fundamental Concepts Used in Geometric Computer Vision
Foundations and Trends® in Computer Graphics and Vision
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Flexible, reconfigurable vision systems can provide the richest sensing modality for sophisticated multiple robot platforms. We propose a cooperative and adaptive approach to vision applied to the problem of finding and protecting humans by a robot team in such emergent circumstances, for example, during a fire in an office building. A panoramic camera system plays an important role in this approach. This report presents the recent progress on the development of vision algorithms based on a panoramic annular lens (PAL) camera system. First, we give a brief survey of existing panoramic camera systems, with an emphasis on geometrical properties of capturing panoramic images from a single-viewpoint. Second, a mathematical model of the panoramic annular lens (PAL) camera that we use is built, and then several issues about camera calibration and image un- warping are addressed. An empirical method is given to roughly ''calibrate" the PAL camera system. Next, a panoramic virtual stereo (PVS) vision approach is proposed, and the problems of self-calibration and real-time 3D estimation are discussed. Finally, we present an experimental system that can detect and track multiple moving objects in real-time using a PAL camera system. The panoramic vision algorithm for moving object tracking also serves the initial step of the PVS approach.