Computational complexity of art gallery problems
IEEE Transactions on Information Theory
Art gallery theorems and algorithms
Art gallery theorems and algorithms
Error Analysis in Stereo Determination of 3-D Point Positions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Information Processing Letters
Automatic Sensor Placement from Vision Task Requirements
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Evaluation of Quantization Error in Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computing the Aspect Graph for Line Drawings of Polyhedral Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
Stochastic Analysis of Stereo Quantization Error
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Bayesian approach to optimal sensor placement
International Journal of Robotics Research
Efficiently Computing and Representing Aspect Graphs of Polyhedral Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computational methods for task-directed sensor data fusion and sensor planning
International Journal of Robotics Research
Computing exact aspect graphs of curved objects: algebraic surfaces
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Recovering shape by purposive viewpoint adjustment
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Optimal sensor and light source positioning for machine vision
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An architecture for multiple perspective interactive video
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Decision-Theoretic Cooperative Sensor Planning
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A tight analysis of the greedy algorithm for set cover
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Error Guided Design of a 3D Vision System
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Sensor planning for 3D object search
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A Solution to the Next Best View Problem for Automated Surface Acquisition
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Tracking Human Motion in Structured Environments Using a Distributed-Camera System
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Learning Patterns of Activity Using Real-Time Tracking
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A Probabilistic Exclusion Principle for Tracking Multiple Objects
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Omnistereo: Panoramic Stereo Imaging
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
Sensor Simulation: Simulation of Cameras in Robot Applications
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Occlusions as a Guide for Planning the Next View
IEEE Transactions on Pattern Analysis and Machine Intelligence
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
The Power of Non-Rectilinear Holes
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CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Integrated Person Tracking Using Stereo, Color, and Pattern Detection
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Using Adaptive Tracking to Classify and Monitor Activities in a Site
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Multi-Camera Multi-Person Tracking for EasyLiving
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Task-oriented generation of visual sensing strategies
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Counting People from Multiple Cameras
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The art gallery theorem: its variations, applications and algorithmic aspects
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Consistent labeling of tracked objects in multiple cameras with overlapping fields of view
IEEE Transactions on Pattern Analysis and Machine Intelligence
Surface Visibility Probabilities in 3D Cluttered Scenes
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Multi-modal and multi-camera attention in smart environments
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IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
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International Journal of Computer Vision
Online control of active camera networks for computer vision tasks
ACM Transactions on Sensor Networks (TOSN)
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Systems utilizing multiple sensors are required in many domains. In this paper, we specifically concern ourselves with applications where dynamic objects appear randomly and the system is employed to obtain some user-specified characteristics of such objects. For such systems, we deal with the tasks of determining measures for evaluating their performance and of determining good sensor configurations that would maximize such measures for better system performance.We introduce a constraint in sensor planning that has not been addressed earlier: visibility in the presence of random occluding objects. occlusion causes random loss of object capture from certain necessitates the use of other sensors that have visibility of this object. Two techniques are developed to analyze such visibility constraints: a probabilistic approach to determine "average" visibility rates and a deterministic approach to address worst-case scenarios. Apart from this constraint, other important constraints to be considered include image resolution, field of view, capture orientation, and algorithmic constraints such as stereo matching and background appearance. Integration of such constraints is performed via the development of a probabilistic framework that allows one to reason about different occlusion events and integrates different multi-view capture and visibility constraints in a natural way. Integration of the thus obtained capture quality measure across the region of interest yields a measure for the effectiveness of a sensor configuration and maximization of such measure yields sensor configurations that are best suited for a given scenario.The approach can be customized for use in many multi-sensor applications and our contribution is especially significant for those that involve randomly occurring objects capable of occluding each other. These include security systems for surveillance in public places, industrial automation and traffic monitoring. Several examples illustrate such versatility by application of our approach to a diverse set of different and sometimes multiple system objectives.