A Complete System for Analysis of Video Lecture Based on Eye Tracking

Xuebai Zhang, Shyan-Ming Yuan*, Ming Dao Chen, Xiao Long Liu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

An eye tracking technology provides a faster and more intuitive interface to explore the learner psychology. In this paper, with the aim of assisting researcher to expand the knowledge of video lectures, we present an efficient system named VLEYE based on eye tracking. The system allows gathering the dynamic areas of interest (AOIs) and combining them with eye movement data. There are mainly three modules in the proposed system, including 'eye movement recorder,' 'dynamic AOI module,' and 'video analyzer.' The 'eye movement recorder' records the eye movement data by eye tracking device, where mouse cursor control function is applied to support the use of low-cost devices. The AOIs could be drawn manually or detected and tracked by the provided algorithm automatically in the 'dynamic AOI module.' The 'video analyzer' provides various visualization modes to view and compare the eye movement information for single or multiple subject, as well as statistical charts and detail fixation information. In addition to performance testing, a case study was conducted to verify the applicability of the proposed system. We demonstrate that this system works well and is an essential step forward in efficiently helping studies to better understand learner cognitive processes for dynamic stimuli within video.

Original languageEnglish
Article number8438455
Pages (from-to)49056-49066
Number of pages11
JournalIEEE Access
Volume6
DOIs
StatePublished - 16 Aug 2018

Keywords

  • Dynamic area of interest (AOI)
  • dynamic stimuli
  • eye movement
  • eye tracking
  • video lecture

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