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ICPR
2010
IEEE

The Detection of Concept Frames Using Clustering Multi-Instance Learning

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The Detection of Concept Frames Using Clustering Multi-Instance Learning
Abstract—The classification of sequences requires the combination of information from different time points. In this paper the detection of facial expressions is considered. Experiments on the detection of certain facial muscle activations in videos show that it is not always required to model the sequences fully, but that the presence of specific frames (the concept frame) can be sufficient for a reliable detection of certain facial expression classes. For the detection of these concept frames a standard classifier is often sufficient, although a more advanced clustering approach performs better in some cases. Keywords-classification, ...
David Tax, Michel Valstar
Added 23 Jun 2010
Updated 23 Jun 2010
Type Conference
Year 2010
Where ICPR
Authors David Tax, Michel Valstar
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