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Towards a video browser for the digital native

Adams, Brett, Greenhill, Stewart and Venkatesh, Svetha 2012, Towards a video browser for the digital native, in ICMEW 2012 : Proceedings of the 13th IEEE International Conference on Multimedia and Expo Workshops, IEEE, Piscataway, N. J., pp. 127-132.

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Title Towards a video browser for the digital native
Author(s) Adams, Brett
Greenhill, Stewart
Venkatesh, Svetha
Conference name IEEE International Conference on Multimedia and Expo. Workshop ( 13th : 2012 : Melbourne, Vic.)
Conference location Melbourne, Vic.
Conference dates 9-13 Jul. 2012
Title of proceedings ICMEW 2012 : Proceedings of the 13th IEEE International Conference on Multimedia and Expo Workshops
Editor(s) [Unknown]
Publication date 2012
Conference series IEEE International Conference on Multimedia and Expo
Start page 127
End page 132
Total pages 6
Publisher IEEE
Place of publication Piscataway, N. J.
Keyword(s) compression
social media
video browsing
visualization
Summary Almost every aspect of how we create, transmit, and consume video has changed, but video interfaces still mimic those from video's inception. We extend Temporal Semantic Compression for interactive video browsing, which uses an arbitrary frame-by-frame interest measure to sub-sample video in real time, with user interface elements that visualize these measures and the effect of compressing on them. We experiment with a novel interest measure for popularity, and design novel visualizations for expressing interest measures and the compression interaction. We conduct the first formative evaluation of the TSC paradigm, with 8 subjects, and report design implications arising from it.
ISBN 9781467320276
9780769547299
Language eng
Field of Research 080305 Multimedia Programming
Socio Economic Objective 890402 Film and Video Services (excl. Animation and Computer Generated Imagery)
HERDC Research category E1 Full written paper - refereed
Persistent URL http://hdl.handle.net/10536/DRO/DU:30049574

Document type: Conference Paper
Collection: Centre for Pattern Recognition and Data Analytics
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