Art gallery theorems and algorithms
Art gallery theorems and algorithms
Art gallery problem with guards whose range of vision is 180°
Computational Geometry: Theory and Applications
Grid Coverage for Surveillance and Target Location in Distributed Sensor Networks
IEEE Transactions on Computers
On the optimal placement of multiple visual sensors
Proceedings of the 4th ACM international workshop on Video surveillance and sensor networks
A design methodology for selection and placement of sensors in multimedia surveillance systems
Proceedings of the 4th ACM international workshop on Video surveillance and sensor networks
Object tracking in the presence of occlusions via a camera network
Proceedings of the 6th international conference on Information processing in sensor networks
Self-orienting wireless multimedia sensor networks for occlusion-free viewpoints
Computer Networks: The International Journal of Computer and Telecommunications Networking
Directional Sensor Placement with Optimal Sensing Range, Field of View and Orientation
WIMOB '08 Proceedings of the 2008 IEEE International Conference on Wireless & Mobile Computing, Networking & Communication
Wireless sensor networks scheduling for full angle coverage
Multidimensional Systems and Signal Processing
Optimal 3-Coverage with Minimum Separation Requirements for Ubiquitous Computing Environments
Mobile Networks and Applications
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The proper placement of visual sensors across a sensor field for covering targets with arbitrary location and orientation is a mission-critical decision in surveillance applications. The specifics of sensor deployment in these applications not only determine the maximum achievable coverage, but it also affects the quality of the target's appearance in cameras for subsequent use in vision tasks. However, the inaccuracies inherent in localization techniques and the lack of knowledge regarding the target orientation render existing proposals insufficient for real-life scenarios. In this paper, we address both challenges. First, we extend the conventional point representation of targets with a circular model to account for full-angle coverage of targets with known location yet with unknown orientation from all directions. We then assume, in the absence of precise location information, a trajectory profile of targets could instead be generated through the importance sampling of the environment, indicating spots where the target is most likely located. This profile-based abstraction enables us to capture the uncertainty in target's location by encircling every agglomeration of proximal samples within one cluster. Each cluster can then be viewed as a virtual macroscopic circular target for which we formulate the coverage problem in terms of a Binary Integer Programming (BIP) model. We have also taken into account the presence of obstruction in between multiple targets by calculating the angles of view of the sensors in an occlusion-dependant manner, effectively determining optimal placement for maximal instead of full-angle coverage. Evaluation results derived from our simulation experiments reveal that the proposed mechanism can effectively achieve high coverage accuracy with minimum number of deployed sensors.