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BACKGROUND Multilocus Sequence Typing (MLST) is a frequently used typing method for the analysis of the clonal relationships among strains of several clinically relevant microbial species. MLST is based on the sequence of housekeeping genes that result in each strain having a distinct numerical allelic profile, which is abbreviated to a unique identifier:(More)
In this paper we describe our TRECVID 2009 video retrieval experiments. The MediaMill team participated in three tasks: concept detection, automatic search, and interactive search. Starting point for the MediaMill concept detection approach is our top-performing bag-of-words system of last year, which uses multiple color descriptors, codebooks with(More)
—In this work a novel approach to video temporal decomposition into semantic units, termed scenes, is presented. In contrast to previous temporal segmentation approaches that employ mostly low-level visual or audiovisual features, we introduce a technique that jointly exploits low-level and high-level features automatically extracted from the visual and the(More)
This paper describes our work on audio event detection, one of our tasks in the European project VIDIVIDEO. Preliminary experiments with a small corpus of sound effects have shown the potential of this type of corpus for training purposes. This paper describes our experiments with SVM classifiers, and different features, using a 290-hour corpus of sound(More)
N-alkanes are long-chain saturated hydrocarbons occurring in plant cuticles that can be used as chemical markers for estimating the diet composition of herbivores. An important constraint of using n-alkanes to estimate diet composition with currently employed mathematical procedures is that the number of markers must be equal or larger than the number of(More)
Extreme drought events and plant invasions are major drivers of global change that can critically affect ecosystem functioning and alter ecosystem-atmosphere exchange. Invaders are expanding worldwide and extreme drought events are projected to increase in frequency and intensity. However, very little is known on how these drivers may interact to affect the(More)
While global characteristics of the speaker's source and spectral features have been successfully employed in pathological voice detection, the underlying text has largely been ignored. In this work, we focus on experiments that exploit the text stimulus that is read by the subject. Features derived from text include the mean cepstral distortion of the(More)
Audio event detection is one of the tasks of the European project VIDIVIDEO. This paper focuses on the detection of non-speech events, and as such only searches for events in audio segments that have been previously classified as non-speech. Preliminary experiments with a small corpus of sound effects have shown the potential of this type of corpus for(More)
This work deals with the problem of automatic temporal segmentation of a video into elementary semantic units known as scenes. Its novelty lies in the use of high-level audio information in the form of audio events for the improvement of scene segmentation performance. More specifically, the proposed technique is built upon a recently proposed audio-visual(More)
This paper summarizes the contributions to semantic video search that can be derived from the audio signal. Because of space restrictions, the emphasis will be on non-linguistic cues. The paper thus covers what is generally known as audio segmentation, as well as audio event detection. Using machine learning approaches, we have built detectors for over 50(More)