Fusion of Region and Point-Feature Detections for Measurement Reconstruction in Multi-Target Kalman Tracking

Conference paper


Michael Teutsch
Wolfgang Krüger
Jürgen Beyerer


Proceedings of the 14th International Conference on Information Fusion, 2011.


14th International Conference on Information Fusion (Fusion), Chicago, Illinois, USA, July 5 - 8, 2011

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 1 millisecond per image. Experimental results are given in example video scenes of an infrared camera located on a buoy for maritime surveillance.