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WWW
2010
ACM
13 years 10 months ago
What are the most eye-catching and ear-catching features in the video?: implications for video summarization
Video summarization is a mechanism for generating short summaries of the video to help people quickly make sense of the content of the video before downloading or seeking more det...
Yaxiao Song, Gary Marchionini, Chi Young Oh
MM
2009
ACM
156views Multimedia» more  MM 2009»
13 years 11 months ago
Understanding near-duplicate videos: a user-centric approach
Popular content in video sharing web sites (e.g., YouTube) is usually duplicated. Most scholars define near-duplicate video clips (NDVC) based on non-semantic features (e.g., di...
Mauro Cherubini, Rodrigo de Oliveira, Nuria Oliver
PR
2008
328views more  PR 2008»
13 years 4 months ago
Activity based surveillance video content modelling
This paper tackles the problem of surveillance video content modelling. Given a set of surveillance videos, the aims of our work are twofold: firstly a continuous video is segment...
Tao Xiang, Shaogang Gong
TRECVID
2007
13 years 5 months ago
The MediaMill TRECVID 2007 Semantic Video Search Engine
In this paper we describe our TRECVID 2007 experiments. The MediaMill team participated in two tasks: concept detection and search. For concept detection we extract regionbased im...
Cees G. M. Snoek, I. Everts, Jan van Gemert, Jan-M...
MM
2003
ACM
120views Multimedia» more  MM 2003»
13 years 9 months ago
Linking multimedia presentations with their symbolic source documents: algorithm and applications
An algorithm is presented that automatically matches images of presentation slides to the symbolic source file (e.g., PowerPointTM or AcrobatTM ) from which they were generated. T...
Berna Erol, Jonathan J. Hull, Dar-Shyang Lee