Visual signatures in video visualization

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Visual signatures in video visualization (2006)

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by Min Chen , Ralf P. Botchen , Rudy R. Hashim , Daniel Weiskopf , Ieee Computer Society , Thomas Ertl , Ieee Computer Society , Ian M. Thornton

Venue:	IEEE Transactions on Visualization and Computer Graphics
Citations:	17 - 9 self

BibTeX

@ARTICLE{Chen06visualsignatures,
    author = {Min Chen and Ralf P. Botchen and Rudy R. Hashim and Daniel Weiskopf and Ieee Computer Society and Thomas Ertl and Ieee Computer Society and Ian M. Thornton},
    title = {Visual signatures in video visualization},
    journal = {IEEE Transactions on Visualization and Computer Graphics},
    year = {2006}
}

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Abstract

Abstract — Video visualization is a computation process that extracts meaningful information from original video data sets and conveys the extracted information to users in appropriate visual representations. This paper presents a broad treatment of the subject, following a typical research pipeline involving concept formulation, system development, a path-finding user study, and a field trial with real application data. In particular, we have conducted a fundamental study on the visualization of motion events in videos. We have, for the first time, deployed flow visualization techniques in video visualization. We have compared the effectiveness of different abstract visual representations of videos. We have conducted a user study to examine whether users are able to learn to recognize visual signatures of motions, and to assist in the evaluation of different visualization techniques. We have applied our understanding and the developed techniques to a set of application video clips. Our study has demonstrated that video visualization is both technically feasible and cost-effective. It has provided the first set of evidence confirming that ordinary users can be accustomed to the visual features depicted in video visualizations, and can learn to recognize visual signatures of a variety of motion events. Index Terms—Video visualization, volume visualization, flow visualization, human factors, user study, visual signatures, video processing, optical flow, GPU rendering. 1

Keyphrases

visual signature video visualization motion event user study extracted information different abstract visual representation concept formulation computation process flow visualization technique visual feature fundamental study appropriate visual representation abstract video visualization flow visualization first set video processing typical research pipeline original video data set different visualization technique human factor developed technique system development meaningful information broad treatment path-finding user study application video clip ordinary user volume visualization first time optical flow index term video visualization field trial real application data

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