Skip to main content

Bionic Tracking: Using Eye Tracking to Track Biological Cells in Virtual Reality

  • Conference paper
  • First Online:
Computer Vision – ECCV 2020 Workshops (ECCV 2020)


We present Bionic Tracking, a novel method for solving biological cell tracking problems with eye tracking in virtual reality using commodity hardware. Using gaze data, and especially smooth pursuit eye movements, we are able to track cells in time series of 3D volumetric datasets. The problem of tracking cells is ubiquitous in developmental biology, where large volumetric microscopy datasets are acquired on a daily basis, often comprising hundreds or thousands of time points that span hours or days. The image data, however, is only a means to an end, and scientists are often interested in the reconstruction of cell trajectories and cell lineage trees. Reliably tracking cells in crowded three-dimensional space over many time points remains an open problem, and many current approaches rely on tedious manual annotation or curation. In the Bionic Tracking approach, we substitute the usual 2D point-and-click interface for annotation or curation with eye tracking in a virtual reality headset, where users follow cells with their eyes in 3D space in order to track them. We detail the interaction design of our approach and explain the graph-based algorithm used to connect different time points, also taking occlusion and user distraction into account. We demonstrate Bionic Tracking using examples from two different biological datasets. Finally, we report on a user study with seven cell tracking experts, highlighting the benefits and limitations of Bionic Tracking compared to point-and-click interfaces.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions


  1. 1.


  1. Amat, F., Höckendorf, B., Wan, Y., Lemon, W.C., McDole, K., Keller, P.J.: Efficient processing and analysis of large-scale light-sheet microscopy data. Nat. Protoc. 10(11) (2015).

  2. Amat, F., et al.: Fast, accurate reconstruction of cell lineages from large-scale fluorescence microscopy data. Nat. Methods 11(9) (2014).

  3. Brooke, J.: SUS - a quick and dirty usability scale. In: Usability Evaluation in Industry, p. 7. CRC Press, June 1996

    Google Scholar 

  4. Bruder, V., Schulz, C., Bauer, R., Frey, S., Weiskopf, D., Ertl, T.: Voronoi-based foveated volume rendering. In: EUROVIS 2019, Porto, Portugal (2019)

    Google Scholar 

  5. Chenouard, N., et al.: Objective comparison of particle tracking methods. Nat. Methods 11(3), 281–289 (2014).

    Article  Google Scholar 

  6. Duchowski, A.T.: Eye Tracking Methodology: Theory and Practice, 3rd edn. Springer, Cham (2017).

    Book  MATH  Google Scholar 

  7. Günther, U., Harrington, K.I.S.: Tales from the trenches: developing sciview, a new 3D viewer for the ImageJ community. In: VisGap - The Gap between Visualization Research and Visualization Software at EuroGraphics/EuroVis 2020, p. 7 (2020).

  8. Gunther, U., et al.: Scenery: flexible virtual reality visualization on the Java VM. In: 2019 IEEE Visualization Conference (VIS), Vancouver, BC, Canada, pp. 1–5. IEEE, October 2019.

  9. Hart, S.G., Staveland, L.E.: Development of NASA-TLX (task load index): results of empirical and theoretical research. Adv. Psychol. 52 (1988).

  10. Huisken, J.: Optical sectioning deep inside live embryos by selective plane illumination microscopy. Science 305(5686) (2004).

  11. Jacob, R.J.K.: Eye tracking in advanced interface design. In: Virtual Environments and Advanced Interface Design, pp. 258–290 (1995)

    Google Scholar 

  12. Kassner, M., Patera, W., Bulling, A.: Pupil: an open source platform for pervasive eye tracking and mobile gaze-based interaction. In: Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing, Seattle, Washington, pp. 1151–1160. ACM Press (2014).

  13. Kennedy, R.S., Lane, N.E., Berbaum, K.S., Lilienthal, M.G.: Simulator sickness questionnaire: an enhanced method for quantifying simulator sickness. Int. J. Aviat. Psychol. 3(3) (1993).

  14. Khamis, M., Oechsner, C., Alt, F., Bulling, A.: VRpursuits: interaction in virtual reality using smooth pursuit eye movements. In: Proceedings of the 2018 International Conference on Advanced Visual Interfaces - AVI 2018, Castiglione della Pescaia, Grosseto, Italy, pp. 1–8. ACM Press (2018).

  15. Klamka, K., Siegel, A., Vogt, S., Göbel, F., Stellmach, S., Dachselt, R.: Look & pedal: hands-free navigation in zoomable information spaces through gaze-supported foot input. In: Proceedings of the 2015 ACM on International Conference on Multimodal Interaction - ICMI 2015, Seattle, Washington, USA, pp. 123–130. ACM Press (2015).

  16. Kosch, T., Hassib, M., Woźniak, P.W., Buschek, D., Alt, F.: Your eyes tell: leveraging smooth pursuit for assessing cognitive workload. In: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems - CHI 2018, Montreal QC, Canada, pp. 1–13. ACM Press (2018).

  17. Kroes, T., Post, F.H., Botha, C.P.: Exposure render: an interactive photo-realistic volume rendering framework. PLoS ONE 7(7) (2012).

  18. Laugwitz, B., Held, T., Schrepp, M.: Construction and evaluation of a user experience questionnaire. In: Holzinger, A. (ed.) USAB 2008. LNCS, vol. 5298, pp. 63–76. Springer, Heidelberg (2008).

    Chapter  Google Scholar 

  19. Levoy, M., Whitaker, R.: Gaze-directed volume rendering. ACM SIGGRAPH Comput. Graph. 24(2) (1990).

  20. Lutz, O.H.-M., Venjakob, A.C., Ruff, S.: SMOOVS: towards calibration-free text entry by gaze using smooth pursuit movements. J. Eye Mov. Res. 8(1) (2015).

  21. Meena, Y.K., Cecotti, H., Wong-Lin, K., Prasad, G.: A multimodal interface to resolve the Midas-Touch problem in gaze controlled wheelchair. In: Conference Proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society, IEEE Engineering in Medicine and Biology Society, Annual Conference 2017 (2017).

  22. Mirhosseini, S., Gutenko, I., Ojal, S., Marino, J., Kaufman, A.: Immersive virtual colonoscopy. IEEE Trans. Visual. Comput. Graph. 25(5) (2019).

  23. Moen, E., Bannon, D., Kudo, T., Graf, W., Covert, M., Van Valen, D.: Deep learning for cellular image analysis. Nat. Methods 16(12), 1233–1246 (2019).

    Article  Google Scholar 

  24. Pietzsch, T., Saalfeld, S., Preibisch, S., Tomancak, P.: BigDataViewer: visualization and processing for large image data sets. 12(6) (2015).

  25. Pitrone, P.G., et al.: OpenSPIM: an open-access light-sheet microscopy platform. Nat. Methods 10(7) (2013).

  26. Piumsomboon, T., Lee, G., Lindeman, R.W., Billinghurst, M.: Exploring natural eye-gaze-based interaction for immersive virtual reality. In: 2017 IEEE Symposium on 3D User Interfaces (3DUI), Los Angeles, CA, USA, pp. 36–39. IEEE (2017).

  27. Reynaud, E.G., Peychl, J., Huisken, J., Tomancak, P.: Guide to light-sheet microscopy for adventurous biologists. Nat. Methods 12(1) (2014).

  28. Schindelin, J., et al.: Fiji: an open-source platform for biological-image analysis. Nat. Methods 9(7) (2012).

  29. Singla, A., Fremerey, S., Robitza, W., Raake, A.: Measuring and comparing QoE and simulator sickness of omnidirectional videos in different head mounted displays. In: 2017 Ninth International Conference on Quality of Multimedia Experience (QoMEX), pp. 1–6, May 2017.

  30. Slater, M., Sanchez-Vives, M.V.: Enhancing our lives with immersive virtual reality. Front. Robot. AI 3 (2016).

  31. Stellmach, S., Dachselt, R.: Look & touch: gaze-supported target acquisition. In: Proceedings of the 2012 ACM Annual Conference on Human Factors in Computing Systems - CHI 2012, Austin, Texas, USA, p. 2981. ACM Press (2012).

  32. Sun, X., Yeoh, W., Koenig, S.: Dynamic fringe-saving A*. In: Proceedings of the 8th International Conference on Autonomous Agents and Multiagent Systems, vol. 2, pp. 891–898. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2009)

    Google Scholar 

  33. Tinevez, J.-Y., et al.: TrackMate: an open and extensible platform for single-particle tracking. Methods 115 (2017). (IEEE Signal Proc. Mag. 23 3 2006)

  34. Ulman, V., et al.: An objective comparison of cell-tracking algorithms. Nat. Methods 14(12), 1141–1152 (2017).

    Article  Google Scholar 

  35. Usher, W., et al.: A virtual reality visualization tool for neuron tracing. IEEE Trans. Visual. Comput. Graph. 24(1) (2017).

  36. Vidal, M., Bulling, A., Gellersen, H.: Pursuits: spontaneous interaction with displays based on smooth pursuit eye movement and moving targets. In: Proceedings of the 2013 ACM International Joint Conference on Pervasive and Ubiquitous Computing - UbiComp 2013, Zurich, Switzerland, p. 439. ACM Press (2013).

  37. Winnubst, J., et al.: Reconstruction of 1,000 projection neurons reveals new cell types and organization of long-range connectivity in the mouse brain. Cell 179(1), 268–281.e13 (2019).

    Article  Google Scholar 

  38. Wolff, C., et al.: Multi-view light-sheet imaging and tracking with the MaMuT software reveals the cell lineage of a direct developing arthropod limb. eLife 7 (2018).

Download references


The authors thank all participants of the user study. Thanks to Mette Handberg-Thorsager for providing the Platynereis dataset and for feedback on the manuscript. Thanks to Vladimir Ulman and Jean-Yves Tinevez for helpful discussions regarding track comparison. Thanks to Bevan Cheeseman, Aryaman Gupta, and Stefanie Schmidt for helpful discussions. Thanks to Pupil Labs for help with the eye tracking calibration.

This work was partially funded by the Center for Advanced Systems Understanding (CASUS), financed by Germany’s Federal Ministry of Education and Research (BMBF) and by the Saxon Ministry for Science, Culture and Tourism (SMWK) with tax funds on the basis of the budget approved by the Saxon State Parliament.

Author information

Authors and Affiliations


Corresponding author

Correspondence to Ulrik Günther .

Editor information

Editors and Affiliations

1 Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (pdf 70 KB)

Supplementary material 2 (pdf 3204 KB)

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Günther, U., Harrington, K.I.S., Dachselt, R., Sbalzarini, I.F. (2020). Bionic Tracking: Using Eye Tracking to Track Biological Cells in Virtual Reality. In: Bartoli, A., Fusiello, A. (eds) Computer Vision – ECCV 2020 Workshops. ECCV 2020. Lecture Notes in Computer Science(), vol 12535. Springer, Cham.

Download citation

  • DOI:

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-66414-5

  • Online ISBN: 978-3-030-66415-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics