2019
DOI: 10.1007/s11042-019-07950-1
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Visual time period analysis: a multimedia analytics application for summarizing and analyzing eye-tracking experiments

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Cited by 3 publications
(3 citation statements)
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“…Consequently, a brief exposure time could lead to different results in terms of comparing different forms of representation. The dynamic analysis of visual behavior could be carried out using the methods proposed in [96], which, on the other hand, underlines the difficulties to be faced when accounting for the time dimension in ET studies. Through the dynamic analysis of visual behavior, it could be possible to study the speed at which videos and pictures tend to drive participants towards focusing on specific AOIs.…”
Section: Discussion and Limitationsmentioning
confidence: 99%
“…Consequently, a brief exposure time could lead to different results in terms of comparing different forms of representation. The dynamic analysis of visual behavior could be carried out using the methods proposed in [96], which, on the other hand, underlines the difficulties to be faced when accounting for the time dimension in ET studies. Through the dynamic analysis of visual behavior, it could be possible to study the speed at which videos and pictures tend to drive participants towards focusing on specific AOIs.…”
Section: Discussion and Limitationsmentioning
confidence: 99%
“…Studying the cross influence of contents and forms in the attractiveness of AOIs; • Introducing means to graphically represent time-dependent phenomena in ET studies across a variety of products, whose exigency is stressed in [88].…”
mentioning
confidence: 99%
“…The rapid growth of multimedia application needs the development of new visualization techniques for analyzing them from different perspectives. Del Fatto et al [11] present a multimedia analytics application for summarizing and analyzing temporal data captured by eye-tracking experiments, while Koivunen-Niemi [13] proposes the use of temporal visualizations for examining differences in media narrative patterns over time and across publications. In particular, they compare co-occurrences of variables in multimedia content chronologically, which can be more useful in identifying patterns and possible biases in media coverage than simply counting the individual occurrences of those variables independently.…”
mentioning
confidence: 99%