Yes / In this paper, we report the results of our recent research into the understanding of the exact distribution of a smile across the face, especially the distinction in the weight distribution of a smile between a genuine and a posed smile. To do this, we have developed a computational framework for the analysis of the dynamic motion of various parts of the face during a facial expression, in particular, for the smile expression. The heart of our dynamic smile analysis framework is the use of optical flow intensity variation across the face during a smile. This can be utilised to efficiently map the dynamic motion of individual regions of the face such as the mouth, cheeks and areas around the eyes. Thus, through our computational framework, we infer the exact distribution of weights of the smile across the face. Further, through the utilisation of two publicly available datasets, namely the CK+ dataset with 83 subjects expressing posed smiles and the MUG dataset with 35 subjects expressing genuine smiles, we show there is a far greater activity or weight distribution around the regions of the eyes in the case of a genuine smile. / Supported in part by the European Union's Horizon 2020 Programme H2020-MSCA-RISE-2017, under the project PDE-GIR with grant number 778035.
| Identifer | oai:union.ndltd.org:BRADFORD/oai:bradscholars.brad.ac.uk:10454/16871 |
| Date | January 2018 |
| Creators | Al-dahoud, Ahmad, Ugail, Hassan |
| Source Sets | Bradford Scholars |
| Language | English |
| Detected Language | English |
| Type | Conference paper, Accepted manuscript |
| Rights | © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
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