Sensor deployment strategy for target detection
WSNA '02 Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications
Wireless sensor networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
Minimal and maximal exposure path algorithms for wireless embedded sensor networks
Proceedings of the 1st international conference on Embedded networked sensor systems
Coverage for target localization in wireless sensor networks
Proceedings of the 5th international conference on Information processing in sensor networks
The sensor selection problem for bounded uncertainty sensing models
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Coverage by randomly deployed wireless sensor networks
IEEE/ACM Transactions on Networking (TON) - Special issue on networking and information theory
Energy-efficient coverage for target detection in wireless sensor networks
Proceedings of the 6th international conference on Information processing in sensor networks
Bounds on coverage and target detection capabilities for models of networks of mobile sensors
ACM Transactions on Sensor Networks (TOSN)
Analysis of target detection performance for wireless sensor networks
DCOSS'05 Proceedings of the First IEEE international conference on Distributed Computing in Sensor Systems
Coverage analysis for target localization in camera sensor networks
Wireless Communications & Mobile Computing
Modeling Coverage in Camera Networks: A Survey
International Journal of Computer Vision
| Hi-index | 0.01 |
Visual coverage is an essential issue in the research on visual sensor networks. However, because of the presence of visual occlusions, the statistics of visual coverage blend the statistics of nodes and targets and are extremely difficult to derive. By assuming the deployment of nodes as a stationary Poisson point process and ignoring boundary effects, this paper presents the first attempt to estimate the probability that an arbitrary target in the field is visually k-covered. The major challenge for the estimation is how to formulate the probability (q) that a node captures a target in its visual range. To tackle this challenge, we first assume a visual detection model that takes visual occlusions into account and then derive several significant statistical parameters of qbased on this model. According to these parameters, we can finally reconstruct the probability density function of qas a combination of a Binomial function and an impulse function. With the estimated coverage statistics, we further propose an estimate of the minimum node density that suffices to ensure a K-coverage across the field.