An eye-tracking database of video advertising

Liu, Hantao ORCID: https://orcid.org/0000-0003-4544-3481 and Leveque, Lucie 2019. An eye-tracking database of video advertising. Presented at: 26th IEEE International Conference on Image Processing (ICIP), Taipei, Taiwan, 22-25 September 2019. 2019 IEEE International Conference on Image Processing (ICIP). IEEE, pp. 425-429. 10.1109/ICIP.2019.8802989

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Abstract

Reliably predicting where people look in images and videos remains challenging and requires substantial eye-tracking data to be collected and analysed for various applications. In this paper, we present an eye-tracking study where twenty-eight participants viewed forty still scenes of video advertising. First, we analyse human attentional behaviour based on gaze data. Then, we evaluate to what extent a machine - saliency model - can predict human behaviour. Experimental results show that there is a significant gap between human and machine in visual saliency. The resulting eye-tracking data would benefit the development of saliency models for video advertising or other relevant applications. The eye-tracking data are made publicly available to the research community.

Item Type:	Conference or Workshop Item - published (Paper)
Date Type:	Published Online
Status:	Published
Schools:	Schools > Computer Science & Informatics
Publisher:	IEEE
ISBN:	978-1-5386-6250-2
ISSN:	1522-4880
Date of First Compliant Deposit:	3 May 2019
Date of Acceptance:	30 April 2019
Last Modified:	14 May 2026 13:45
URI:	https://orca.cardiff.ac.uk/id/eprint/122157

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