Predicting primary gaze behavior using social saliency fields

Hyun Soo Park, Eakta Jain, Yaser Sheikh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

22 Scopus citations

Abstract

We present a method to predict primary gaze behavior in a social scene. Inspired by the study of electric fields, we posit "social charges'-latent quantities that drive the primary gaze behavior of members of a social group. These charges induce a gradient field that defines the relationship between the social charges and the primary gaze direction of members in the scene. This field model is used to predict primary gaze behavior at any location or time in the scene. We present an algorithm to estimate the time-varying behavior of these charges from the primary gaze behavior of measured observers in the scene. We validate the model by evaluating its predictive precision via cross-validation in a variety of social scenes.

Original languageEnglish (US)
Title of host publicationProceedings - 2013 IEEE International Conference on Computer Vision, ICCV 2013
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3503-3510
Number of pages8
ISBN (Print)9781479928392
DOIs
StatePublished - Jan 1 2013
Event2013 14th IEEE International Conference on Computer Vision, ICCV 2013 - Sydney, NSW, Australia
Duration: Dec 1 2013Dec 8 2013

Publication series

NameProceedings of the IEEE International Conference on Computer Vision

Other

Other2013 14th IEEE International Conference on Computer Vision, ICCV 2013
CountryAustralia
CitySydney, NSW
Period12/1/1312/8/13

Keywords

  • Gaze prediction
  • Social scene understanding

Fingerprint Dive into the research topics of 'Predicting primary gaze behavior using social saliency fields'. Together they form a unique fingerprint.

  • Cite this

    Park, H. S., Jain, E., & Sheikh, Y. (2013). Predicting primary gaze behavior using social saliency fields. In Proceedings - 2013 IEEE International Conference on Computer Vision, ICCV 2013 (pp. 3503-3510). [6751547] (Proceedings of the IEEE International Conference on Computer Vision). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCV.2013.435