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A novel method for robust object tracking with K-means clustering using histogram back-projection technique

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Abstract

This paper presents a novel and fast method for k-means clustering based object tracking for coloured frames, based on histogram back-projection method. The proposed method uses histogram equalization for finding centroid of the object for each frame. As from the information transfer aspect, this study improves the tracking performance using Bhattacharya Coefficient with the method of histogram back-projection including k-means clustering. Histogram back-projection computes the probability of the object of interest and the clustering process classifies high-performance regions. In addition, a mean shift tracking method is used to monitor the object after the histogram back-projection process, which provides better tracking for fast-moving objects. The proposed mean shift algorithm also provides gradient ascent. In addition, this method is invariant to clutter and camera motion; pose changes and faster tracking. Simulated results show that the proposed method gives better tracking results than other conventional methods while having a lower computational demand. Therefore it is highlighted that the proposed method would have a significant contribution in the field of object tracking.

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Acknowledgments

This study was performed at Gazi University, Engineering Faculty, Electrical & Electronics Engineering Department. Uğurhan KUTBAY performed the K-Mean process and Bhattacharyya Coefficient. In addition, Uğurhan KUTBAY discussed & reported the images and participated in the sequence alignment and drafted the manuscript with İsa ŞAHİN. Anıl AKYEL and Fırat HARDALAÇ created the study hypothesis with Uğurhan KUTBAY and helped to draft the manuscript. İsa ŞAHIN participated in the alignment sequence and evaluated the algorithms. The final editing of manuscript is carried out by Anıl AKYEL. All authors read and approved the final manuscript.

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Authors and Affiliations

  1. Department of Electrical & Electronics Engineering, Faculty of Engineering, Gazi University, Ankara, Turkey

    Fırat Hardalaç, Uğurhan Kutbay, İsa Şahin & Anıl Akyel

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  1. Fırat Hardalaç
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  2. Uğurhan Kutbay
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  3. İsa Şahin
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  4. Anıl Akyel
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Correspondence to Anıl Akyel.

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Hardalaç, F., Kutbay, U., Şahin, İ. et al. A novel method for robust object tracking with K-means clustering using histogram back-projection technique. Multimed Tools Appl 77, 24059–24072 (2018). https://doi.org/10.1007/s11042-018-5661-x

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  • DOI: https://doi.org/10.1007/s11042-018-5661-x

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