Signal, Image and Video Processing

, Volume 12, Issue 6, pp 1097–1105 | Cite as

Efficient multiple moving object detection and tracking using combined background subtraction and clustering

  • H. S. G. SupreethEmail author
  • Chandrashekar M. Patil
Original Paper


Object detection and tracking is a fundamental, challenging task in computer vision because of the difficulties in tracking. Continuous deformation of objects during movement and background clutter leads to poor tracking. In this paper, a method of multiple moving object detection and tracking by combining background subtraction and K-means clustering is proposed. The proposed method can handle objects occlusion, shadows and camera jitter. Background subtraction filters irrelevant information, and K-means clustering is employed to select the moving object from the remaining information, and it is capable of handling merging and splitting of moving objects using spatial information. Experimental results show that the proposed method is robust when compared to other techniques.


Object detection Background subtraction K-means clustering Object tracking 


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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2018

Authors and Affiliations

  1. 1.SJB Institute of TechnologyBangaloreIndia
  2. 2.Vidya Vardhaka College of EngineeringMysoreIndia

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