Managing video collections at large

Abstract

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. MOTIVATIONSVideo data processing has for long been of high interest for the development of compression and efficient transmission algorithms. In parallel, the domain of content-based multimedia retrieval has developed, initially from text retrieval, then for images and now addressing video content retrieval. Whereas in text and image retrieval the volume of data and associated access techniques are well under control, this is largely not the case for video collection management. Not only video data volume may rapidly grow complex and huge but it also requires efficient access techniques associated to the temporal aspect of the data.Efforts in video content modeling such as MPEG-7 [9] are providing a base for the solution to the problem of handling large amount of multimedia data. While such a model is very well suited to represent a single multimedia document, it cannot be used efficiently for accessing, querying and managing a large collection of such documents due to its inherent complexity. Unfortunately, most video retrieval systems presented in state of the art literature [1, 4] do not explicitely discuss the way they address such management Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. CVDB '04 Paris, France Copyright 2004 ACM 1-58113-917-9/04/06 ...$5.00. issues.In this paper, we detail the framework we have constructed for the management of video document collections in the context of our research in video content analysis. Rather than presenting a temporal document model alone, our ultimate goal is to develop content characterization and indexing algorithms for the management of large video collections. When addressing such problems, one rapidly faces the need for a favorable context on which to base these developments and also that permits rapid and objective evaluation of research findings. From an extensible multimedia...

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