Looking at the viewer: analysing facial activity to detect personal highlights of multimedia contents

  • Authors:

  • Hideo Joho;Jacopo Staiano;Nicu Sebe;Joemon M. Jose

  • Affiliations:

  • Department of Library, Information and Media Studies, University of Tsukuba, Tsukuba, Japan 305-8550;Department of Information Engineering and Computer Science, University of Trento, Povo, Italy 38100;Department of Information Engineering and Computer Science, University of Trento, Povo, Italy 38100;School of Computing Science, University of Glasgow, Glasgow, UK G12 8QQ

  • Venue:
  • Multimedia Tools and Applications
  • Year:
  • 2011

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Abstract

This paper presents an approach to detect personal highlights in videos based on the analysis of facial activities of the viewer. Our facial activity analysis was based on the motion vectors tracked on twelve key points in the human face. In our approach, the magnitude of the motion vectors represented a degree of a viewer's affective reaction to video contents. We examined 80 facial activity videos recorded for ten participants, each watching eight video clips in various genres. The experimental results suggest that useful motion vectors to detect personal highlights varied significantly across viewers. However, it was suggested that the activity in the upper part of face tended to be more indicative of personal highlights than the activity in the lower part.