Our main focus for this year was on setting up a flexible retrieval environment rather than on evaluating novel video retrieval approaches. We experimented with feature detectors based on visual information only, and compared Weibull-based and GMM-based detectors, and found large differences across topics. Some models are good for one topic other for the next. Future research has to show whether a combined approach is useful. In the search task we focused on a seamless integration of our visual and textual retrieval system, to allow for easy multimodal querying. We use the NEXI language for querying and RAM for specifying visual retrieval models We experimented with a generic retrieval approach that used collection specific information only for training the high-level feature detectors. Runs making use of textual information perform around the median, adding visual information does not influence the results.

Text REtrieval Conference
Database Architectures

Westerveld, T., van Gemert, J. C., Cornacchia, R., Hiemstra, D., & de Vries, A. (2005). An integrated approach to text and image retrieval - The Lowlands Team at Trecvid. In Proceedings of TREC Video Retrieval Evaluation 2005 (TRECVID ) (pp. 1–12).