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.
In a recent paper REF Tax et al. explored the question of whether it is always necessary to fully model the entire sequence, or whether the presence of specific frames, called 'concept frames', might be sufficient for reliable detection of facial expressions.
The Detection of Concept Frames Using Clustering Multi-instance Learning
2010 20th International Conference on Pattern Recognition
2010 20th International Conference on Pattern Recognition
Computer Science