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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Teutsch, M. Kruger, W. Beyerer, J. |
| Copyright Year | 2011 |
| Description | Author affiliation: Fraunhofer IOSB, Fraunhoferstr. 1, 76131 Karlsruhe, Germany (Teutsch, M.; Kruger, W.; Beyerer, J.) |
| Abstract | Object tracking in 2D video surveillance image data is one of the key needs for many follow-up operations such as object classification or activity recognition. In scenes with multiple objects crossing each other's way, there is a high potential for split and merge detections disturbing the tracking process. In these situations, it is helpful or even necessary to reconstruct the object-related measurements to support tracking approaches such as Kalman or Particle Filter. We present a way of fusing three different detection approaches taking benefit from their specific advantages to reconstruct measurements, if a split or merge situation is recognized. The resulting split and merge handling shows better results than using each detection approach individually without fusion. Furthermore, the tracking process is fast with a computation time less than one millisecond per image. Experimental results are given in example video scenes of an infrared camera located on a buoy for maritime surveillance. |
| Starting Page | 1 |
| Ending Page | 8 |
| File Size | 1366766 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781457702679 |
| e-ISBN | 9780982443828 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-07-05 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Intl Society of Info Fusion |
| Subject Keyword | Kalman filters Tracking Image reconstruction Sea measurements Feature extraction Boats Current measurement infrared video multitarget tracking (MTT) Kalman filter split and merge handling multiple features maritime object tracking vessel surveillance |
| Content Type | Text |
| Resource Type | Article |
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