ACMMM 2014, 22nd ACM International Conference on Multimedia, November 3-7, 2014, Orlando, Florida, USA
This paper introduces a framework for establishing links between related media fragments within a collection of videos. A set of analysis techniques is applied for extracting information from dierent types of data. Visual-based shot and scene segmentation is performed for dening media fragments at dierent granularity levels, while visual cues are detected from keyframes of the video via concept detection
and optical character recognition (OCR). Keyword extraction is applied on textual data such as the output of OCR, subtitles and metadata. This set of results is used for the
automatic identication and linking of related media fragments. The proposed framework exhibited competitive performance in the Video Hyperlinking sub-task of MediaEval
2013, indicating that video scene segmentation can provide more meaningful segments, compared to other decomposition methods, for hyperlinking purposes.
Type:
Conférence
City:
Orlando
Date:
2014-11-03
Department:
Data Science
Eurecom Ref:
4398
Copyright:
© ACM, 2014. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ACMMM 2014, 22nd ACM International Conference on Multimedia, November 3-7, 2014, Orlando, Florida, USA http://dx.doi.org/10.1145/2647868.2655041
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