Tracking a moving object with a binary sensor network
Proceedings of the 1st international conference on Embedded networked sensor systems
Distributed particle filters for sensor networks
Proceedings of the 3rd international symposium on Information processing in sensor networks
Distributed state representation for tracking problems in sensor networks
Proceedings of the 3rd international symposium on Information processing in sensor networks
A line in the sand: a wireless sensor network for target detection, classification, and tracking
Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue: Military communications systems and technologies
MCMC-Based Particle Filtering for Tracking a Variable Number of Interacting Targets
IEEE Transactions on Pattern Analysis and Machine Intelligence
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
On target tracking with binary proximity sensors
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Proceedings of the 4th international conference on Embedded networked sensor systems
A distributed algorithm for managing multi-target identities in wireless ad-hoc sensor networks
IPSN'03 Proceedings of the 2nd international conference on Information processing in sensor networks
IEEE Communications Magazine
Energy-Efficient Tracking of Continuous Objects in Wireless Sensor Networks
UIC '08 Proceedings of the 5th international conference on Ubiquitous Intelligence and Computing
On the Deterministic Tracking of Moving Objects with a Binary Sensor Network
DCOSS '08 Proceedings of the 4th IEEE international conference on Distributed Computing in Sensor Systems
Location-Free Object Tracking on Graph Structures
EuroSSC '08 Proceedings of the 3rd European Conference on Smart Sensing and Context
Target Counting under Minimal Sensing: Complexity and Approximations
Algorithmic Aspects of Wireless Sensor Networks
A Sensor Network System for Measuring Traffic in Short-Term Construction Work Zones
DCOSS '09 Proceedings of the 5th IEEE International Conference on Distributed Computing in Sensor Systems
Target tracking with binary proximity sensors
ACM Transactions on Sensor Networks (TOSN)
Distributive target tracking in sensor networks with a Markov random field model
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Distributed energy-efficient target tracking with binary sensor networks
ACM Transactions on Sensor Networks (TOSN)
Energy efficient cluster-based target tracking strategy
HONET'09 Proceedings of the 6th international conference on High capacity optical networks and enabling technologies
On collaborative tracking of a target group using binary proximity sensors
Journal of Parallel and Distributed Computing
Differential forms for target tracking and aggregate queries in distributed networks
Proceedings of the sixteenth annual international conference on Mobile computing and networking
Minimalist counting in sensor networks (Noise helps)
Ad Hoc Networks
Multiple-Target Tracking With Binary Proximity Sensors
ACM Transactions on Sensor Networks (TOSN)
Analysis of Deterministic Tracking of Multiple Objects Using a Binary Sensor Network
ACM Transactions on Sensor Networks (TOSN)
On topology of sensor networks deployed for tracking
WASA'11 Proceedings of the 6th international conference on Wireless algorithms, systems, and applications
Practical data compression in wireless sensor networks: A survey
Journal of Network and Computer Applications
Trajectory mining from anonymous binary motion sensors in Smart Environment
Knowledge-Based Systems
Differential forms for target tracking and aggregate queries in distributed networks
IEEE/ACM Transactions on Networking (TON)
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Recent work has shown that, despite the minimal information provided by a binary proximity sensor, a network of such sensors can provide remarkably good target tracking performance. In this paper, we examine the performance of such a sensor network for tracking multiple targets. We begin with geometric arguments that address the problem of counting the number of distinct targets, given a snapshot of the sensor readings. We provide necessary and sufficient criteria for an accurate target count in a one-dimensional setting, and provide a greedy algorithm that determines the minimum number of targets that is consistent with the sensor readings. While these combinatorial arguments bring out the difficulty of target counting based on sensor readings at a given time, they leave open the possibility of accurate counting and tracking by exploiting the evolution of the sensor readings across time. To this end, we develop a particle filtering algorithm based on a cost function that penalizes changes in velocity. An extensive set of simulations, as well as experiments with passive infrared sensors, are reported. We conclude that, despite the combinatorial complexity of target counting, probabilistic approaches based on fairly generic models for the trajectories yield respectable tracking performance.