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Multimedia Tools and Applications

, Volume 77, Issue 22, pp 30067–30088 | Cite as

Single object tracking using particle filter framework and saliency-based weighted color histogram

  • Mai Thanh Nhat Truong
  • Myeongsuk Pak
  • Sanghoon KimEmail author
Article

Abstract

Despite many years of research, object tracking remains a challenging problem, not only because of the variety of object appearances, but also because of the complexity of surrounding environments. In this research, we present an algorithm for single object tracking using a particle filter framework and color histograms. Particle filters are iterative algorithms that perform predictions in each iteration using particles, which are samples drawn from a statistical distribution. Color histograms are embedded in these particles, and the distances between histograms are used to measure likelihood between targets and observations. One downside of color histograms is that they ignore spatial information, which may produce tracking failure when objects appear that are similar in color. To overcome this disadvantage, we propose a saliency-based weighting scheme for histogram calculation. Given an image region, first its saliency map is generated. Next, its histogram is calculated based on the generated saliency map. Pixels located in salient regions have higher weights than those in others, which helps preserve the spatial information. Experimental results showed the efficiency of the proposed appearance model in object tracking under various conditions.

Keywords

Object tracking Particle filter Color histogram Saliency map 

Notes

Funding

This study was funded by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2015R1D1A1A01057518).

Compliance with Ethical Standards

Conflict of interests

The authors declare that they have no conflict of interests.

Ethical Approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Supplementary material

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Mai Thanh Nhat Truong
    • 1
  • Myeongsuk Pak
    • 1
  • Sanghoon Kim
    • 1
    Email author
  1. 1.Department of Electrical, Electronic, and Control EngineeringHankyong National UniversityGyeonggi-doRepublic of Korea

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