Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1145/1236360.1236427 | IPSN |
Keywords | Field | DocType |
accurate target count,respectable tracking performance,multiple target,distinct target,sensor reading,sensor network,accurate counting,binary proximity sensor,good target tracking performance,passive infrared sensor,infrared,cost function,greedy algorithm,particle filter,radar tracking,wireless sensor networks,sensor networks,greedy algorithms,theory,radar imaging,particle filters,algorithms,magnetometers | Computer vision,Proximity sensor,Computer science,Particle filter,Combinatorial complexity,Greedy algorithm,Artificial intelligence,Probabilistic logic,Snapshot (computer storage),Wireless sensor network,Binary number | Conference |
Citations | PageRank | References |
92 | 3.77 | 13 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jaspreet Singh Suri | 1 | 337 | 29.90 |
| Upamanyu Madhow | 2 | 3025 | 293.76 |
| Rajiv Kumar | 3 | 154 | 20.75 |
| Subhash Suri | 4 | 5255 | 455.58 |
| Richard E. Cagley | 5 | 119 | 6.77 |