Name
Abstract | ||
|---|---|---|
In this paper, we consider a variant of the multi-target tracking problem in which the tracking region is divided into zones and targets can only be monitored as they transition between these zones. We call this the transition tracking problem. The key challenge in Transition Tracking is to estimate the number of targets in the tracking region without being able to sense all targets simultaneously. In this paper, we propose an approach to the Transition Tracking problem called TransTrack. Unlike most other tracking algorithms that maximize the likelihood of the sensor data, TransTrack applies penalty functions to find the minimum number of targets that can explain the sensor data. These penalties allow tracks with larger numbers of targets only ifthey have sufficiently fewer errors than other, alternative tracks. To evaluate this approach, we apply TransTrack to a data set containing 3275 transitions between rooms in a home. We observe an average room tracking accuracy of up to 94.5%. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/DCOSS.2016.27 | 2016 International Conference on Distributed Computing in Sensor Systems (DCOSS) |
Keywords | Field | DocType |
TransTrack,transition tracking problem,multitarget tracking problem,zone transition,tracking algorithms,penalty functions | Computer vision,Radar tracker,Computer science,Tracking system,Artificial intelligence,Signal processing algorithms | Conference |
ISSN | ISBN | Citations |
2325-2936 | 978-1-5090-1461-3 | 2 |
PageRank | References | Authors |
0.38 | 11 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Avinash Kalyanaraman | 1 | 34 | 4.81 |
| Erin Griffiths | 2 | 65 | 4.37 |
| Kamin Whitehouse | 3 | 1982 | 160.79 |