Expression Recognition Using the Periocular Region: A Feasibility Study
2019 (English)In: Proceedings - 14th International Conference on Signal Image Technology and Internet Based Systems, SITIS 2018, Institute of Electrical and Electronics Engineers Inc. , 2019, 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.
Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2019. p. 536-541
Keywords [en]
Emotion recognition, Expression recognition, Periocular analysis, Periocular descriptor, Descriptors, Feasibility studies, Full face method, Image descriptors, Periocular, Spatial-temporal data
National Category
Natural Sciences
Identifiers
URN: urn:nbn:se:ri:diva-38895DOI: 10.1109/SITIS.2018.00087Scopus ID: 2-s2.0-85065903319ISBN: 9781538693858 (print)OAI: oai:DiVA.org:ri-38895DiVA, id: diva2:1321986
Conference
14th International Conference on Signal Image Technology and Internet Based Systems, SITIS 2018, 26 November 2018 through 29 November 2018
Note
Funding details: Vetenskapsrådet; Funding text 1: Author F. A.-F. thanks the Swedish Research Council for funding his research. Authors acknowledge the CAISR program and the SIDUS-AIR project of the Swedish Knowledge Foundation.
2019-06-102019-06-102020-01-23Bibliographically approved