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Multiple target tracking with lazy background subtraction and connected components analysis

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Abstract

Background subtraction, binary morphology, and connected components analysis are the first processing steps in many vision-based tracking applications. Although background subtraction has been the subject of much research, it is typically treated as a stand-alone process, dissociated from the subsequent phases of object recognition and tracking. This paper presents a method for decreasing computational cost in visual tracking systems by using track state estimates to direct and constrain image segmentation via background subtraction and connected components analysis. We also present a multiple target tracking application that uses the technique to achieve a large reduction in computation costs.

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Authors and Affiliations

  1. Sandia National Labs, MS 1188, PO Box 5800, Albuquerque, NM, 87185, USA

    Robert G. Abbott

  2. Department of Computer Science, University of New Mexico, Albuquerque, NM, 87131, USA

    Lance R. Williams

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  1. Robert G. Abbott
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  2. Lance R. Williams
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Correspondence to Robert G. Abbott.

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Abbott, R.G., Williams, L.R. Multiple target tracking with lazy background subtraction and connected components analysis. Machine Vision and Applications 20, 93–101 (2009). https://doi.org/10.1007/s00138-007-0109-8

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  • DOI: https://doi.org/10.1007/s00138-007-0109-8

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