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Clustering of Gaze During Dynamic Scene Viewing is Predicted by Motion

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Abstract

Where does one attend when viewing dynamic scenes? Research into the factors influencing gaze location during static scene viewing have reported that low-level visual features contribute very little to gaze location especially when opposed by high-level factors such as viewing task. However, the inclusion of transient features such as motion in dynamic scenes may result in a greater influence of visual features on gaze allocation and coordination of gaze across viewers. In the present study, we investigated the contribution of low- to mid-level visual features to gaze location during free-viewing of a large dataset of videos ranging in content and length. Signal detection analysis on visual features and Gaussian Mixture Models for clustering gaze was used to identify the contribution of visual features to gaze location. The results show that mid-level visual features including corners and orientations can distinguish between actual gaze locations and a randomly sampled baseline. However, temporal features such as flicker, motion, and their respective contrasts were the most predictive of gaze location. Additionally, moments in which all viewers’ gaze tightly clustered in the same location could be predicted by motion. Motion and mid-level visual features may influence gaze allocation in dynamic scenes, but it is currently unclear whether this influence is involuntary or due to correlations with higher order factors such as scene semantics.

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  1. ICC.1: 2001-4, www.color.org.

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Acknowledgments

The authors would like to thank members of the Edinburgh Visual Cognition laboratory including Antje Nuthmann and George Malcolm for their comments and feedback, and Josie Landback for running experiments. This project was funded by the Leverhulme Trust (Ref F/00-158/BZ) and the ESRC (RES-062-23-1092) awarded to John M. Henderson.

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Authors and Affiliations

  1. Department of Computing Goldsmiths, University of London, London, UK

    Parag K. Mital

  2. Department of Psychological Sciences, Birkbeck, University of London, London, UK

    Tim J. Smith

  3. Department of Psychology, School of Philosophy, Psychology and Language Sciences, University of Edinburgh, Edinburgh, UK

    Robin L. Hill

  4. Department of Psychology and McCausland Center for Brain Imaging, University of South Carolina, Columbia, SC, USA

    John M. Henderson

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  1. Parag K. Mital
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Correspondence to Parag K. Mital.

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All eye-movement data and visualization tools can be obtained from: http://thediemproject.wordpress.com.

Appendices

Appendix 1

See Table 3.

Table 3 List of videos used in this study
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Appendix 2

Continuation of Fig. 6.

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Mital, P.K., Smith, T.J., Hill, R.L. et al. Clustering of Gaze During Dynamic Scene Viewing is Predicted by Motion. Cogn Comput 3, 5–24 (2011). https://doi.org/10.1007/s12559-010-9074-z

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