Video viewer state estimation using gaze tracking and video content analysis

Jae Woo Kim, Jong Ok Kim

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

1 Citation (Scopus)

Abstract

In this paper, we propose a novel viewer state model based on gaze tracking and video content analysis. There are two primary contributions in this paper. We first improve gaze state classification significantly by combining video content analysis. Then, based on the estimated gaze state, we propose a novel viewer state model indicating both viewer's interest and existence of viewer's ROIs. Experiments were conducted to verify the performance of the proposed gaze state classifier and viewer state model. The experimental results show that the use of video content analysis in gaze state classification considerably improves the classification results and consequently, the viewer state model correctly estimates the interest state of video viewers.

Original languageEnglish
Title of host publicationIEEE VCIP 2013 - 2013 IEEE International Conference on Visual Communications and Image Processing
DOIs
Publication statusPublished - 2013
Event2013 IEEE International Conference on Visual Communications and Image Processing, IEEE VCIP 2013 - Kuching, Sarawak, Malaysia
Duration: 2013 Nov 172013 Nov 20

Publication series

NameIEEE VCIP 2013 - 2013 IEEE International Conference on Visual Communications and Image Processing

Other

Other2013 IEEE International Conference on Visual Communications and Image Processing, IEEE VCIP 2013
Country/TerritoryMalaysia
CityKuching, Sarawak
Period13/11/1713/11/20

Keywords

  • gaze state classification
  • gaze tracking
  • region of interest
  • video viewing
  • viewer state

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition

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