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Fusion of region and point-feature detections for measurement reconstruction in multi-target Kalman tracking

: Teutsch, Michael; Krüger, Wolfgang; Beyerer, Jürgen

Volltext urn:nbn:de:0011-n-1927805 (1.2 MByte PDF)
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Erstellt am: 1.2.2012

Dunham, Darin ; Institute of Electrical and Electronics Engineers -IEEE-; International Society of Information Fusion -ISIF-:
14th International Conference on Information Fusion 2011. Proceedings : Chicago, Illinois, USA, 5 - 8 July 2011
Piscataway, NJ: IEEE, 2011
ISBN: 978-1-4577-0267-9
ISBN: 978-0-9824438-2-8
8 S.
International Conference on Information Fusion (FUSION) <14, 2011, Chicago/Ill.>
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IOSB ()
multitarget tracking (MTT); Kalman filter; split and merge handling; multiple feature; maritime object tracking; vessel surveillance; infrared video

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.