The flooding time synchronization protocol
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
Topology Inference for a Vision-Based Sensor Network
CRV '05 Proceedings of the 2nd Canadian conference on Computer and Robot Vision
Distributed localization of networked cameras
Proceedings of the 5th international conference on Information processing in sensor networks
Coordinate-free Coverage in Sensor Networks with Controlled Boundaries via Homology
International Journal of Robotics Research
Determining vision graphs for distributed camera networks using feature digests
EURASIP Journal on Applied Signal Processing
Bridging the gaps between cameras
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Automated multi-camera planar tracking correspondence modeling
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Recovering network topology with binary sensors
Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems
A fuzzy model for coverage evaluation of cameras and multi-camera networks
Proceedings of the Fourth ACM/IEEE International Conference on Distributed Smart Cameras
A distributed topological camera network representation for tracking applications
IEEE Transactions on Image Processing - Special section on distributed camera networks: sensing, processing, communication, and implementation
Traffic modeling and prediction using sensor networks: Who will go where and when?
ACM Transactions on Sensor Networks (TOSN)
Visual sensor network lifetime maximization by prioritized scheduling of nodes
Journal of Network and Computer Applications
A low-bandwidth camera sensor platform with applications in smart camera networks
ACM Transactions on Sensor Networks (TOSN)
Modeling Coverage in Camera Networks: A Survey
International Journal of Computer Vision
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Camera networks are widely used for tasks such as surveillance, monitoring and tracking. In order to accomplish these tasks, knowledge of localization information such as camera locations and other geometric constraints about the environment (e.g. walls, rooms, and building layout) are typically considered to be essential. However, this information is not required for tasks such as estimating the topology of camera network coverage, or coordinate-free object tracking and navigation. In this paper, we propose a simplicial representation (called CN-Complex) that can be constructed from discrete local observations, and utilize this novel representation to recover topological information of the network coverage. We prove that our representation captures the correct topological information for coverage in 2.5D layouts, and demonstrate its utility in simulations as well as an experimental setup. Our proposed approach is particularly useful in the context of ad-hoc camera networks in indoor/outdoor urban environments with distributed but limited computational power and energy.