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,
2) the exploration of bag-of-words for event detection, and
3) the selection of informative concepts out of 1,346 concept detectors as a representation for event detection.
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.