Automatic Sensor Placement from Vision Task Requirements
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special Issue on Industrial Machine Vision and Computer Vision Technology:8MPart
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Optimal Camera Placement to Obtain Accurate 3D Point Positions
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 1 - Volume 1
Automatic Multi-Camera Setup Optimization for Optical Tracking
VR '06 Proceedings of the IEEE conference on Virtual Reality
Tele-immersive environments for rehabilitation activities: an empirical study on proprioception
Multidimensional Systems and Signal Processing
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With the advent of virtual spaces, there has been a need to integrate physical world with virtual spaces. The integration can be achieved by real-time 3D imaging using stereo cameras followed by fusion of virtual and physical space information. Systems that enable such information fusions over several geographically distributed locations are called tele-immersive and should be easily deployed. The optimal placement of 3D cameras becomes the key to achieving high quality 3D information about physical spaces. In this paper, we present an optimization framework for automating the placement of multiple stereo cameras in an application specific manner. The framework eliminates ad-hoc experimentations and sub-optimal camera placements for end applications by running our simulation code. The camera placement problem is formulated as optimization problem over continuous physical space with the objective function based on 3D information error and a set of constraints that generalize application specific requirements. The novelty of our work lies in developing the theoretical optimization framework under spatially varying resolution requirements and in demonstrating improved camera placements with our framework in comparison with other placement techniques.