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Expression Recognition Using the Periocular Region: A Feasibility Study
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.ORCID iD: 0000-0002-1400-346X
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.ORCID iD: 0000-0002-4929-1262
RISE Viktoria, Gothenburg, Sweden.ORCID iD: 0000-0002-1043-8773
2018 (English)In: Proceedings. The 14th International Conference on Signal Image Technology & Internet Based Systems: SITIS 2018 / [ed] DiBaja, G. S., Gallo, L., Yetongnon, K., Dipanda, A., CastrillonSantana, M., Chbeir, R., Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 536-541Conference paper, Published paper (Refereed)
Abstract [en]

This paper investigates the feasibility of using the periocular region for expression recognition. Most works have tried to solve this by analyzing the whole face. Periocular is the facial region in the immediate vicinity of the eye. It has the advantage of being available over a wide range of distances and under partial face occlusion, thus making it suitable for unconstrained or uncooperative scenarios. We evaluate five different image descriptors on a dataset of 1,574 images from 118 subjects. The experimental results show an average/overall accuracy of 67.0/78.0% by fusion of several descriptors. While this accuracy is still behind that attained with full-face methods, it is noteworthy to mention that our initial approach employs only one frame to predict the expression, in contraposition to state of the art, exploiting several order more data comprising spatial-temporal data which is often not available. ©2018 IEEE

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018. p. 536-541
Keywords [en]
Expression Recognition, Emotion Recognition, Periocular Analysis, Periocular Descriptor
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:hh:diva-41501DOI: 10.1109/SITIS.2018.00087ISI: 000469258400076Scopus ID: 2-s2.0-85065903319ISBN: 978-1-5386-9385-8 (electronic)ISBN: 978-1-5386-9386-5 (print)OAI: oai:DiVA.org:hh-41501DiVA, id: diva2:1391031
Conference
14th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS 2018), Las Palmas de Gran Canaria, Spain, November 26-29, 2018
Funder
Swedish Research CouncilAvailable from: 2020-02-03 Created: 2020-02-03 Last updated: 2020-02-03Bibliographically approved

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