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
Automatic sensor placement for accurate dimensional inspection
Computer Vision and Image Understanding
Automatic Camera Placement for Image-Based Modeling
PG '99 Proceedings of the 7th Pacific Conference on Computer Graphics and Applications
Range-free localization schemes for large scale sensor networks
Proceedings of the 9th annual international conference on Mobile computing and networking
Optimal Camera Placement for Automated Surveillance Tasks
Journal of Intelligent and Robotic Systems
Multi-Camera Human Activity Monitoring
Journal of Intelligent and Robotic Systems
A sensor placement approach for the monitoring of indoor scenes
EuroSSC'07 Proceedings of the 2nd European conference on Smart sensing and context
Automatic sensor placement for model-based robot vision
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
An event driven framework for assistive CPS environments
ACM SIGBED Review - Special Issue on the 2nd Joint Workshop on High Confidence Medical Devices, Software, and Systems (HCMDSS) and Medical Device Plug-and-Play (MD PnP) Interoperability
A tool for sensor placement and system monitoring in assistive environments
Proceedings of the 4th International Conference on PErvasive Technologies Related to Assistive Environments
Special Section on CAD/Graphics 2013: Geometric multi-covering
Computers and Graphics
Hi-index | 0.00 |
Given a 3D environment, a set of constraints, and a set of sensor models, this paper addresses the problem of finding the set of sensors and their corresponding placement that covers a target space in the environment. The set of possible sensors is represented in a parametric space associated with the sensor's pose. Initially, the target space is discretized as a set of space elements. A voting scheme builds an accumulator array where each space element votes for all sensors that may observe it while satisfying the perceptual constraints. A heuristic selects the best set of cameras that covers the target space. We present experimental results with synthetic and realistic 3D models.