Alan F. Smeaton

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The TREC Video Retrieval Evaluation (TRECVid)is an international benchmarking activity to encourage research in video information retrieval by providing a large test collection, uniform scoring procedures, and a forum for organizations 1 interested in comparing their results. TRECVid completed its fifth annual cycle at the end of 2005 and in 2006 TRECVid(More)
The Text Retrieval Conference’s (TREC’s) Video Retrieval Evaluation (TRECVID) 2010 was a TRECstyle video analysis and retrieval evaluation, the goal of which remains to promote progress in contentbased exploitation of digital video via open, metricsbased evaluation. Over the last 10 years this effort has yielded a better understanding of how systems can(More)
This paper provides an overview of a pilot evaluation of video summaries using rushes from several BBC dramatic series. It was carried out under the auspices of TRECVID. Twenty-two research teams submitted video summaries of up to 4% duration, of 42 individual rushes video files aimed at compressing out redundant and insignificant material. The output of(More)
In this paper we propose the use of WordNet as a knowledge base in an information retrieval task. The application areas range from information filtering and document retrieval to multimedia retrieval and data sharing in large scale distributed database systems. The WordNet derived knowledge base makes semantic knowledge available which can be used in(More)
Shot boundary detection (SBD) is the process of automatically detecting the boundaries between shots in video. It is a problem which has attracted much attention since video became available in digital form as it is an essential pre-processing step to almost all video analysis, indexing, summarisation, search, and other contentbased operations. Automatic(More)
The TREC Video Retrieval Evaluation (TRECVID) 2012 was a TREC-style video analysis and retrieval evaluation, the goal of which remains to promote progress in content-based exploitation of digital video via open, metrics-based evaluation. Over the last ten years this effort has yielded a better understanding of how systems can effectively accomplish such(More)
Microblogs as a new textual domain offer a unique proposition for sentiment analysis. Their short document length suggests any sentiment they contain is compact and explicit. However, this short length coupled with their noisy nature can pose difficulties for standard machine learning document representations. In this work we examine the hypothesis that it(More)
*Successful and effective content-based access to digital video requires fast, accurate and scalable methods to determine the video content automatically. A variety of contemporary approaches to this rely on text taken from speech within the video, or on matching one video frame against others using low-level characteristics like colour, texture, or shapes,(More)