This paper reports on an investigation into the scholarly impact of the TRECVid (TREC Video Retrieval Evaluation) benchmarking conferences between 2003 and 2009. The contribution ...
Clare Thornley, Andrea C. Johnson, Alan F. Smeaton...
This work proposes a model for video retrieval based upon the inference network model. The document network is constructed using video metadata encoded using MPEG-7 and captures i...
Motivated by the increasing popularity of video on handheld devices and the resulting importance for effective video retrieval, this paper revisits the relevance of thumbnails in ...
Video contains multiple types of audio and visual information, which are difficult to extract, combine or trade-off in general video information retrieval. This paper provides an ...
In this paper we describe our TRECVID 2008 video retrieval experiments. The MediaMill team participated in three tasks: concept detection, automatic search, and interactive search...
Cees G. M. Snoek, Koen E. A. van de Sande, Ork de ...
Situated models of meaning ground words in the non-linguistic context, or situation, to which they refer. Applying such models to sports video retrieval requires learning appropri...
Storyboards, a grid layout of thumbnail images as surrogates representing video, have received much attention in video retrieval interfaces and published studies through the years...
Extraction and utilization of high-level semantic features are critical for more effective video retrieval. However, the performance of video retrieval hasn't benefited much d...
Abstract. We combine in this paper automatic learning of a large lexicon of semantic concepts with traditional video retrieval methods into a novel approach to narrow the semantic ...
Cees Snoek, Marcel Worring, Dennis Koelma, Arnold ...
Abstract. Recent research in video retrieval has focused on automated, highlevel feature indexing on shots or frames. One important application of such indexing is to support preci...
Shi-Yong Neo, Jin Zhao, Min-Yen Kan, Tat-Seng Chua