Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/13141
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dc.contributor.authorAlshamsi, H-
dc.contributor.authorMeng, H-
dc.contributor.authorLi, M-
dc.coverage.spatialChangsha, China-
dc.date.accessioned2016-09-14T10:12:03Z-
dc.date.available2016-08-15-
dc.date.available2016-09-14T10:12:03Z-
dc.date.issued2016-
dc.identifier.citation12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD 2016), pp. 2161 - 2166, Changsha, China, (13-15 August 2016)en_US
dc.identifier.urihttp://icnc-fskd.hnu.edu.cn/-
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/13141-
dc.description.abstractFacial expression has made significant progress in recent years with many commercial systems are available for real-world applications. It gains strong interest to implement a facial expression system on a portable device such as tablet and smart phone device using the camera already integrated in the devices. It is very common to see face recognition phone unlocking app in new smart phones which are proven to be hassle free way to unlock a phone. Implementation a facial expression system in a smart phone would provide fun applications that can be used to measure the mood of the user in their daily life or as a tool for their daily monitoring of the motion in phycology studies. However, traditional facial expression algorithms are normally computing extensive and can only be implemented offline at a computer. In this paper, a novel automatic system has been proposed to recognize emotions from face images on a smart phone in real-time. In our system, the camera of the smart phone is used to capture the face image, BRIEF features are extracted and k-nearest neighbor algorithm is implemented for the classification. The experimental results demonstrate that the proposed facial expression recognition on mobile phone is successful and it gives up to 89.5% recognition accuracy.en_US
dc.description.sponsorshipThe work of Hongying Meng was supported by Brunel Research Initiative & Enterprise Fund on the project entitled “Automatic Emotional State Detection and Analysis on Embedded Devices”. This research is also partially supported by the 973 project on Network Big Data Analytics funded by the Ministry of Science and Technology, China. No. 2014CB340404.en_US
dc.format.extent2161 - 2166-
dc.language.isoenen_US
dc.source12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)-
dc.source12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)-
dc.subjectMachine learningen_US
dc.subjectFacial expressionen_US
dc.subjectImage processingen_US
dc.subjectMobile computingen_US
dc.titleReal time facial expression recognition App development on mobile phonesen_US
dc.typeConference Paperen_US
pubs.finish-date2016-08-15-
pubs.finish-date2016-08-15-
pubs.publication-statusPublished-
pubs.start-date2016-08-13-
pubs.start-date2016-08-13-
Appears in Collections:Dept of Electronic and Computer Engineering Research Papers

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