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The MediaMill TRECVID 2011 Semantic Video Search Engine

In this paper we describe our TRECVID 2011 video retrieval experiments. The MediaMill team participated in two tasks: semantic indexing, and multimedia event detection. The starting point for the MediaMill detection approach is our top-performing bag-of-words system of TRECVID 2010, which uses multiple color SIFT descriptors, sparse codebooks with spatial pyramids, and kernel-based machine learning. All supported by GPU-optimized algorithms, approximated histogram intersection kernels, and multi-frame video processing. This year our experiments focus on 1) the soft assignment of descriptors with the use of difference coding and 2) the utility of 1,346 concept detectors for event retrieval. The 2011 edition of the TRECVID benchmark has again been a fruitful participation for the MediaMill team, resulting in the runner-up ranking for concept detection in the semantic indexing task.

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