Automatic viewing control for 3D direct manipulation
I3D '92 Proceedings of the 1992 symposium on Interactive 3D graphics
CamDroid: a system for implementing intelligent camera control
I3D '95 Proceedings of the 1995 symposium on Interactive 3D graphics
Intelligent camera control for graphical environments
Intelligent camera control for graphical environments
Intelligent multi-shot visualization interfaces for dynamic 3D worlds
IUI '99 Proceedings of the 4th international conference on Intelligent user interfaces
The hemi-cube: a radiosity solution for complex environments
SIGGRAPH '85 Proceedings of the 12th annual conference on Computer graphics and interactive techniques
Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence
Parisian camera placement for vision metrology
Pattern Recognition Letters - Special issue: Evolutionary computer vision and image understanding
Automated camera layout to satisfy task-specific and floor plan-specific coverage requirements
Computer Vision and Image Understanding - Special issue on omnidirectional vision and camera networks
Automatic sensor placement in a 3D volume
Proceedings of the 2nd International Conference on PErvasive Technologies Related to Assistive Environments
Can you see me now? sensor positioning for automated and persistent surveillance
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Genetic algorithm and pure random search for exosensor distribution optimisation
International Journal of Bio-Inspired Computation
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Within the framework of a French project, which aims at developing a new human presence sensor, we intend to design a sensor system simulator. During the establishment of the requirements of that new sensor we raised that the mission of a global scene survey could only be performed by a collection of several systems using very diverse technologies. This article presents the development of a method for the placement of multi-technology and multisensor systems. The considered environments are room or set of rooms in office buildings or individual homes. We will explain how we managed to represent the use of different sensors considering their various environments. Then, the way of exploiting these models using genetic algorithms is discussed. Those models are oriented for finding system placement and therefore for helping sensor networks deployment.