This article presents an overview of the video copy detection benchmark which was run over a period of 4 years (2008--2011) as part of the TREC Video Retrieval (TRECVID) workshop series. The main contributions of the article include i) an examination of the evolving design of the evaluation framework and its components (system tasks, data, measures); ii) a high-level overview of results and best-performing approaches; and iii) a discussion of lessons learned over the four years. The content-based copy detection (CCD) benchmark worked with a large collection of synthetic queries, which is atypical for TRECVID, as was the use of a normalized detection cost framework. These particular evaluation design choices are motivated and appraised.

This panel will debate various approaches to improving video search, and explore how professional cataloguing, crowd sourced metadata, and improvements in search algorithms will evolve over the next ten years. Panelists will explore the needs of large scale video archives, and compare these against the current capabilities of video search.

This paper is a summary of the 2008 TRECVid Event Detection evaluation track. TRECVid is a laboratory-style evaluation that aims to model real world situations or significant component tasks. The event detection evaluation was organized to address detection of a set of specific events that would be of potential interest to an operator in the surveillance domain. This paper describes the video data, evaluation tasks, evaluation metrics, and results of the event detection evaluation.

TRECVID is an annual exercise which encourages research in information retrieval from digital video by providing a large video test collection, uniform scoring procedures, and a forum for organizations interested in comparing their results. TRECVID benchmarking covers both interactive and manual searching by end users, as well as the benchmarking of some supporting technologies including shot boundary detection, extraction of some semantic features, and the automatic segmentation of TV news broadcasts into non-overlapping news stories. TRECVID has a broad range of over 40 participating groups from across the world and as it is now (2004) in its 4th annual cycle it is opportune to stand back and look at the lessons we have learned from the cumulative activity. In this paper we shall present a brief and high-level overview of the TRECVID activity covering the data, the benchmarked tasks, the overall results obtained by groups to date and an overview of the approaches taken by selective groups in some tasks. While progress from one year to the next cannot be measured directly because of the changing nature of the video data we have been using, we shall present a summary of the lessons we have learned from TRECVID and include some pointers on what we feel are the most important of these lessons.

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Article Free Access Share on Comparing interactive information retrieval systems across sites: the TREC-6 interactive track matrix experiment Authors: Eric Lagergren Statistical Engineering Division, National Institute of Standards and Technology (NIST), Gaithersburg, MD Statistical Engineering Division, National Institute of Standards and Technology (NIST), Gaithersburg, MDView Profile , Paul Over Information Access and User Interfaces Division, National Institute of Standards and Technology (NIST), Gaithersburg, MD Information Access and User Interfaces Division, National Institute of Standards and Technology (NIST), Gaithersburg, MDView Profile Authors Info & Claims SIGIR '98: Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrievalAugust 1998 Pages 164–172https://doi.org/10.1145/290941.290986Online:01 August 1998Publication History 43citation637DownloadsMetricsTotal Citations43Total Downloads637Last 12 Months10Last 6 weeks3 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF