Art gallery theorems and algorithms
Art gallery theorems and algorithms
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
A Bayesian approach to optimal sensor placement
International Journal of Robotics Research
Computational methods for task-directed sensor data fusion and sensor planning
International Journal of Robotics Research
Recovering shape by purposive viewpoint adjustment
International Journal of Computer Vision - Special issue on active vision II
Optimal sensor and light source positioning for machine vision
Computer Vision and Image Understanding
Computing Occlusion-Free Viewpoints
IEEE Transactions on Pattern Analysis and Machine Intelligence
Decision-Theoretic Cooperative Sensor Planning
IEEE Transactions on Pattern Analysis and Machine Intelligence
Sensor planning for 3D object search
Computer Vision and Image Understanding
Tracking Human Motion in Structured Environments Using a Distributed-Camera System
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning Patterns of Activity Using Real-Time Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
Constraint-Based Sensor Planning for Scene Modeling
IEEE Transactions on Pattern Analysis and Machine Intelligence
A randomized art-gallery algorithm for sensor placement
SCG '01 Proceedings of the seventeenth annual symposium on Computational geometry
M2Tracker: A Multi-View Approach to Segmenting and Tracking People in a Cluttered Scene
International Journal of Computer Vision
Occlusions as a Guide for Planning the Next View
IEEE Transactions on Pattern Analysis and Machine Intelligence
Task-oriented generation of visual sensing strategies
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Global search methods for solving nonlinear optimization problems
Global search methods for solving nonlinear optimization problems
A General Method for Sensor Planning in Multi-Sensor Systems: Extension to Random Occlusion
International Journal of Computer Vision
Consistent labeling of tracked objects in multiple cameras with overlapping fields of view
IEEE Transactions on Pattern Analysis and Machine Intelligence
Active vision in robotic systems: A survey of recent developments
International Journal of Robotics Research
Optimal camera placement to measure distances regarding static and dynamic obstacles
International Journal of Sensor Networks
Modeling Coverage in Camera Networks: A Survey
International Journal of Computer Vision
Pipeline-Architecture Based Real-Time Active-Vision for Human-Action Recognition
Journal of Intelligent and Robotic Systems
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Vision systems for various tasks are increasingly being deployed. Although significant effort has gone into improving the algorithms for such tasks, there has been relatively little work on determining optimal sensor configurations. This paper addresses this need. We specifically address and enhance the state-of-the-art in the analysis of scenarios where there are dynamically occuring objects capable of occluding each other. The visibility constraints for such scenarios are analyzed in a multi-camera setting. Also analyzed are other static constraints such as image resolution and field-of-view, and algorithmic requirements such as stereo reconstruction, face detection and background appearance. Theoretical analysis with the proper integration of such visibility and static constraints leads to a generic framework for sensor planning, which can then be customized for a particular task. Our analysis can be applied to a variety of applications, especially those involving randomly occuring objects, and include surveillance and industrial automation. Several examples illustrate the wide applicability of the approach.