Details
| Original language | English |
|---|---|
| Pages (from-to) | 1317-1335 |
| Number of pages | 19 |
| Journal | ISPRS International Journal of Geo-Information |
| Volume | 4 |
| Issue number | 3 |
| Publication status | Published - 6 Aug 2015 |
Abstract
Tracking moving objects is both challenging and important for a large variety of applications. Different technologies based on the global positioning system (GPS) and video or radio data are used to obtain the trajectories of the observed objects. However, in some use cases, they fail to provide sufficiently accurate, complete and correct data at the same time. In this work we present an approach for fusing GPS-and video-based tracking in order to exploit their individual advantages. In this way we aim to combine the reliability of GPS tracking with the high geometric accuracy of camera detection. For the fusion of the movement data provided by the different devices we use a hidden Markov model (HMM) formulation and the Viterbi algorithm to extract the most probable trajectories. In three experiments, we show that our approach is able to deal with challenging situations like occlusions or objects which are temporarily outside the monitored area. The results show the desired increase in terms of accuracy, completeness and correctness.
Keywords
- Algorithm, Object tracking, Trajectory analysis, sensor and data fusion
ASJC Scopus subject areas
- Social Sciences(all)
- Geography, Planning and Development
- Earth and Planetary Sciences(all)
- Computers in Earth Sciences
- Earth and Planetary Sciences(all)
- Earth and Planetary Sciences (miscellaneous)
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In: ISPRS International Journal of Geo-Information, Vol. 4, No. 3, 06.08.2015, p. 1317-1335.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - GPS-aided video tracking
AU - Feuerhake, Udo
AU - Brenner, Claus
AU - Sester, Monika
PY - 2015/8/6
Y1 - 2015/8/6
N2 - Tracking moving objects is both challenging and important for a large variety of applications. Different technologies based on the global positioning system (GPS) and video or radio data are used to obtain the trajectories of the observed objects. However, in some use cases, they fail to provide sufficiently accurate, complete and correct data at the same time. In this work we present an approach for fusing GPS-and video-based tracking in order to exploit their individual advantages. In this way we aim to combine the reliability of GPS tracking with the high geometric accuracy of camera detection. For the fusion of the movement data provided by the different devices we use a hidden Markov model (HMM) formulation and the Viterbi algorithm to extract the most probable trajectories. In three experiments, we show that our approach is able to deal with challenging situations like occlusions or objects which are temporarily outside the monitored area. The results show the desired increase in terms of accuracy, completeness and correctness.
AB - Tracking moving objects is both challenging and important for a large variety of applications. Different technologies based on the global positioning system (GPS) and video or radio data are used to obtain the trajectories of the observed objects. However, in some use cases, they fail to provide sufficiently accurate, complete and correct data at the same time. In this work we present an approach for fusing GPS-and video-based tracking in order to exploit their individual advantages. In this way we aim to combine the reliability of GPS tracking with the high geometric accuracy of camera detection. For the fusion of the movement data provided by the different devices we use a hidden Markov model (HMM) formulation and the Viterbi algorithm to extract the most probable trajectories. In three experiments, we show that our approach is able to deal with challenging situations like occlusions or objects which are temporarily outside the monitored area. The results show the desired increase in terms of accuracy, completeness and correctness.
KW - Algorithm
KW - Object tracking
KW - Trajectory analysis, sensor and data fusion
UR - http://www.scopus.com/inward/record.url?scp=84948959319&partnerID=8YFLogxK
U2 - 10.3390/ijgi4031317
DO - 10.3390/ijgi4031317
M3 - Article
AN - SCOPUS:84948959319
VL - 4
SP - 1317
EP - 1335
JO - ISPRS International Journal of Geo-Information
JF - ISPRS International Journal of Geo-Information
SN - 2220-9964
IS - 3
ER -