The MediaMill TRECVID 2008 Semantic Video Search Engine

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. Rather than continuing to increase the number of concept detectors available for retrieval, our TRECVID 2008 experiments focus on increasing the robustness of a small set of detectors using a bag-of-words approach. To that end, our concept detection experiments emphasize in particular the role of visual sampling, the value of color invariant features, the influence of codebook construction, and the effectiveness of kernel-based learning parameters. For retrieval, a robust but limited set of concept detectors necessitates the need to rely on as many auxiliary information channels as possible. Therefore, our automatic search experiments focus on predicting which information channel to trust given a certain topic, leading to a novel framework for predictive video retrieval. To improve the video retrieval resul...

• Type: Conference
• Year: 2008
• Where: TRECVID
• Authors: Cees G. M. Snoek, Koen E. A. van de Sande, Ork de Rooij, Bouke Huurnink, Jan van Gemert, Jasper R. R. Uijlings, Jiyin He, Xirong Li, I. Everts, Vladimir Nedovic, M. van Liempt, Richard van Balen, Maarten de Rijke, Jan-Mark Geusebroek, Theo Gevers, Marcel Worring, Arnold W. M. Smeulders, Dennis Koelma, Fei Yan, Muhammad Atif Tahir, Krystian Mikolajczyk, Josef Kittler
• Keywords: Concept Detection, Interactive Search, Internet Technology, TRECVID 2008, Video Retrieval