Managing Video Collections at Large
Nicolas Moënne-Loccoz, Viper Group, Computer Vision and Multimedia
Lab, University of Geneva
Bruno Janvier, Viper Group, Computer
Vision and Multimedia Lab, University of Geneva
Stéphane
Marchand-Maillet, Viper Group, Computer Vision and Multimedia Lab,
University of Geneva
Eric Bruno, Viper Group, Computer Vision and
Multimedia Lab, University of Geneva
Video document retrieval is now an active part of the domain of multimedia retrieval. However, unlike for other media, the management of a collection of video documents adds the problem of efficiently handling an overwhelming volume of temporal data. Challenges include balancing efficient content modeling and storage against fast access at various levels. In this paper, we detail the framework we have built to accommodate our developments in content-based multimedia retrieval. We show that not only our framework facilitates the developments of processing and indexing algorithms but it also opens the way to several other possibilities such as rapid interface prototyping or retrieval algorithms benchmarking. In this respect, we discuss our developments in relation to wider contexts such as MPEG-7 and the TREC Video Track.