We address the problem of automatic interpretation of nonexaggerated human facial and body behaviours captured in video. We illustrate our approach by three examples. (1) We intro...
Current state-of-the-art systems for automatic phonetic transcription (APT) are mostly phone recognizers based on Hidden Markov models (HMMs). We present a different approach for ...
Christina Leitner, Martin Schickbichler, Stefan Pe...
The Hierarchical Hidden Markov Model (HHMM) is a well formalized tool suitable to model complex patterns in long temporal or spatial sequences. Even if effective algorithms are ava...
ion when we annotate content. This therefore requires us to investigate and model video semantics. Because of the type and volume of data, general-purpose approaches are likely to ...
Abstract. The use of high level information in source separation algorithms can greatly constrain the problem and lead to improved results by limiting the solution space to semanti...