How to Distinguish Posed from Spontaneous Smiles using Geometric Features


Valstar, Michel F. and Gunes, Hatice and Pantic, Maja (2007) How to Distinguish Posed from Spontaneous Smiles using Geometric Features. In: 9th International Conference on Multimodal Interfaces, ICMI 2007, 12-15 November 2007, Nagoya, Japan (pp. pp. 38-45).

[img] PDF
Restricted to UT campus only
: Request a copy
Abstract:Automatic distinction between posed and spontaneous expressions is an unsolved problem. Previously cognitive sciences' studies indicated that the automatic separation of posed from spontaneous expressions is possible using the face modality alone. However, little is known about the information contained in head and shoulder motion. In this work, we propose to (i) distinguish between posed and spontaneous smiles by fusing the head, face, and shoulder modalities, (ii) investigate which modalities carry important information and how the information of the modalities relate to each other, and (iii) to which extent the temporal dynamics of these signals attribute to solving the problem. We use a cylindrical head tracker to track the head movements and two particle filtering techniques to track the facial and shoulder movements. Classification is performed by kernel methods combined with ensemble learning techniques. We investigated two aspects of multimodal fusion: the level of abstraction (i.e., early, mid-level, and late fusion) and the fusion rule used (i.e., sum, product and weight criteria). Experimental results from 100 videos displaying posed smiles and 102 videos displaying spontaneous smiles are presented. Best results were obtained with late fusion of all modalities when 94.0% of the videos were classified correctly.
Item Type:Conference or Workshop Item
Copyright:© 2007 ACM
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

Metis ID: 245908