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A visual object tracking benchmark for cell motility in time-lapse imaging

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Abstract

Automatic tracking of cells is a widely studied problem in various biomedical applications. Although there are numerous approaches for the video object tracking task in different contexts, the performance of these methods depends on many factors regarding the specific application they are used for. This paper presents a comparative study that specifically targets cell tracking problem and compares performance behavior of the recent algorithms. We propose a framework for the performance evaluation of the tracking algorithms and compare several state-of-the-art object tracking approaches on an extensive time-lapse inverted microscopy dataset. We report the quantitative evaluations of the algorithms based on success rate and precision performance metrics.

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Notes

  1. DSST Source Code: http://www.cvl.isy.liu.se/en/research/objrec/visualtracking/scalvistrack/DSST_code.zip.

  2. FCT Source Code: http://www4.comp.polyu.edu.hk/~cslzhang/FCT/FCT.htm.

  3. IVT Source Code: http://www.cs.toronto.edu/~dross/ivt/.

  4. KCF Source Code: https://github.com/vojirt/kcf.

  5. L1APG Source Code: https://github.com/lukacu/visual-tracking-matlab/tree/master/l1apg.

  6. MILTrack Source Code: https://github.com/lukacu/mil.

  7. MOSSE Source Code: https://github.com/albertoQD/tracking-mosse.

  8. ODFS Source Code: http://www4.comp.polyu.edu.hk/~cslzhang/ODFS/ODFS.htm.

  9. SRDCF Source Code: https://www.cvl.isy.liu.se/en/research/objrec/visualtracking/regvistrack/.

  10. Staple Source Code: https://github.com/bertinetto/staple.

  11. LADCF Source Code: http://www.votchallenge.net/vot2018/trackers.html.

  12. GOTURN Source Code: https://github.com/foolwood/GOTURN_matconvnet.

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Authors and Affiliations

  1. Microelectronics, Guidance and Electro-Optics Business Sector, Aselsan, 06750, Ankara, Turkey

    H. Seckin Demir

  2. Department of Electrical and Computer Engineering, University of Illinois at Chicago, Chicago, IL, 60607, USA

    A. Enis Cetin

  3. Cancer Systems Biology Laboratory, Graduate School of Informatics, METU, 06800, Ankara, Turkey

    Rengul Cetin Atalay

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  1. H. Seckin Demir
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  2. A. Enis Cetin
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  3. Rengul Cetin Atalay
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Correspondence to Rengul Cetin Atalay.

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Demir, H.S., Cetin, A.E. & Cetin Atalay, R. A visual object tracking benchmark for cell motility in time-lapse imaging. SIViP 13, 1063–1070 (2019). https://doi.org/10.1007/s11760-019-01443-2

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