Evaluation campaigns and TRECVid
Top Cited Papers
- 26 October 2006
- proceedings article
- Published by Association for Computing Machinery (ACM)
- p. 321-330
- https://doi.org/10.1145/1178677.1178722
Abstract
The TREC Video Retrieval Evaluation (TRECVid) is an international benchmarking activity to encourage research in video information retrieval by providing a large test col- lection, uniform scoring procedures, and a forum for orga- nizations 1 interested in comparing their results. TRECVid completed its fifth annual cycle at the end of 2005 and in 2006 TRECVid will involve almost 70 research organiza- tions, universities and other consortia. Throughout its ex- istence, TRECVid has benchmarked both interactive and automatic/manual searching for shots from within a video corpus, automatic detection of a variety of semantic and low-level video features, shot boundary detection and the detection of story boundaries in broadcast TV news. This paper will give an introduction to information retrieval (IR) evaluation from both a user and a system perspective, high- lighting that system evaluation is by far the most prevalent type of evaluation carried out. We also include a summary of TRECVid as an example of a system evaluation bench- marking campaign and this allows us to discuss whether such campaigns are a good thing or a bad thing. There are arguments for and against these campaigns and we present some of them in the paper concluding that on balance they have had a very positive impact on research progress.Keywords
This publication has 6 references indexed in Scilit:
- The Semantic Pathfinder: Using an Authoring Metaphor for Generic Multimedia IndexingIEEE Transactions on Pattern Analysis and Machine Intelligence, 2006
- Introduction to the Special Issue on INEXInformation Retrieval Journal, 2005
- Early versus late fusion in semantic video analysisPublished by Association for Computing Machinery (ACM) ,2005
- The Use and Utility of High-Level Semantic Features in Video RetrievalLecture Notes in Computer Science, 2005
- Successful approaches in the TREC video retrieval evaluationsPublished by Association for Computing Machinery (ACM) ,2004
- On the detection of semantic concepts at TRECVIDPublished by Association for Computing Machinery (ACM) ,2004