dc.contributor.author | Benli, Kristin Surpuhi | en_US |
dc.contributor.author | Eskil, Mustafa Taner | en_US |
dc.date.accessioned | 2015-11-24T14:06:23Z | |
dc.date.available | 2015-11-24T14:06:23Z | |
dc.date.issued | 2014-12-04 | |
dc.identifier.citation | Benli, K. S. & Eskil, M. T. (2014). Extraction and selection of muscle based features for facial expression recognition. Paper presented at the 2014 22nd International Conference on Pattern Recognition, 1651-1656. doi:10.1109/ICPR.2014.14 | en_US |
dc.identifier.isbn | 9781479952083 | |
dc.identifier.issn | 1051-4651 | |
dc.identifier.uri | https://hdl.handle.net/11729/719 | |
dc.identifier.uri | http://dx.doi.org/10.1109/ICPR.2014.14 | |
dc.description.abstract | In this study we propose a new set of muscle activity based features for facial expression recognition. We extract muscular activities by observing the displacements of facial feature points in an expression video. The facial feature points are initialized on muscular regions of influence in the first frame of the video. These points are tracked through optical flow in sequential frames. Displacements of feature points on the image plane are used to estimate the 3D orientation of a head model and relative displacements of its vertices. We model the human skin as a linear system of equations. The estimated deformation of the wireframe model produces an over-determined system of equations that can be solved under the constraint of the facial anatomy to obtain muscle activation levels. We apply sequential forward feature selection to choose the most descriptive set of muscles for recognition of basic facial expressions. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | IEEE Computer Soc | en_US |
dc.relation.isversionof | 10.1109/ICPR.2014.14 | |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Image sequences | en_US |
dc.subject | Face detection | en_US |
dc.subject | Motion | en_US |
dc.subject | Models | en_US |
dc.subject | Face | en_US |
dc.subject | Face recognition | en_US |
dc.subject | Feature extraction | en_US |
dc.subject | Mathematical model | en_US |
dc.subject | Muscles | en_US |
dc.subject | Shape | en_US |
dc.subject | 3D orientation estimation | en_US |
dc.subject | Facial expression recognition | en_US |
dc.subject | Linear system | en_US |
dc.subject | Muscle activity | en_US |
dc.subject | Muscle based features extraction | en_US |
dc.subject | Muscle based features selection | en_US |
dc.subject | Muscular regions | en_US |
dc.subject | Optical flow | en_US |
dc.subject | Sequential frames | en_US |
dc.subject | Feature selection | en_US |
dc.title | Extraction and selection of muscle based features for facial expression recognition | en_US |
dc.type | conferenceObject | en_US |
dc.description.version | Publisher's Version | en_US |
dc.description.version | Author Post Print | en_US |
dc.relation.journal | 2014 22nd International Conference on Pattern Recognition | en_US |
dc.contributor.department | Işık Üniversitesi, Mühendislik Fakültesi, İnşaat Mühendisliği Bölümü | en_US |
dc.contributor.department | Işık University, Faculty of Engineering, Department of Civil Engineering | en_US |
dc.contributor.department | Işık Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü | en_US |
dc.contributor.department | Işık University, Faculty of Engineering, Department of Computer Engineering | en_US |
dc.contributor.authorID | 0000-0001-6282-6703 | |
dc.contributor.authorID | 0000-0003-0298-0690 | |
dc.identifier.startpage | 1651 | |
dc.identifier.endpage | 1656 | |
dc.peerreviewed | Yes | en_US |
dc.publicationstatus | Published | en_US |
dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
dc.contributor.institutionauthor | Benli, Kristin Surpuhi | en_US |
dc.contributor.institutionauthor | Eskil, Mustafa Taner | en_US |
dc.relation.index | WOS | en_US |
dc.relation.index | Scopus | en_US |
dc.relation.index | Conference Proceedings Citation Index – Science (CPCI-S) | en_US |
dc.description.wosid | WOS:000359818001130 | |