Computer Science

Computer Science ›› 2018, Vol. 45 ›› Issue (8): 253-257.doi: 10.11896/j.issn.1002-137X.2018.08.045

• Graphics, Image & Pattern Recognition • Previous Articles     Next Articles

Multi-object Tracking Algorithm Based on Kalman Filter

ZHAO Guang-hui, ZHUO Song, XU Xiao-long   

  1. School of Computer Science and Technology,Wuhan University of Technology,Wuhan 430070,China
  • Received:2017-12-30 Online:2018-08-29 Published:2018-08-29

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Abstract: Aiming at the tracking failure caused by occlusion between objects,interleaving or target drift in multi-object tracking,this paper proposed an occlusion prediction tracking algorithm based on Kalman filter and spatiograms.By combining the color histogram and the distribution of color in space,spatiograms can be used to distinguish different objects,so that the object can still be tracked when interleaving or occlusion between objects occurs.The state of the object can be predicted by the Kalman filtering algorithm.The occlusion mark is usedfor the object which overlaps with other objects,so that the occluded object which is undetected can be tracked in the next frame.The 2D MOT 2015 data set was used for experiment.The average accuracy of tracking achieves 34.1%.Experimental results show that the algorithm can improve the performance of multi-object tracking.

Key words: Kalman filter, Multi-object tracking, Occlusion prediction, Spatial color histogram

CLC Number: 

  • TP391.41
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