The detection of concept frames using Clustering Multi-Instance Learning


Tax, D.M.J. and Hendriks, E. and Valstar, M.F. and Pantic, M. (2010) The detection of concept frames using Clustering Multi-Instance Learning. In: 20th International Conference on Pattern Recognition, ICPR 2010, 23-26 August 2010, Istanbul, Turkey (pp. pp. 2917-2920).

open access
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.
Item Type:Conference or Workshop Item
Copyright:© 2010 IEEE
Electrical Engineering, Mathematics and Computer Science (EEMCS)
Research Group:
Link to this item:
Official URL:
Export this item as:BibTeX
HTML Citation
Reference Manager


Repository Staff Only: item control page