Towards More Robust Automatic Facial Expression Recognition in Smart Environments

被引：13

作者：

Bernin, Arne ^{[1
,2
]}

Mueller, Larissa ^{[1
,2
]}

Ghose, Sobin ^{[1
]}

von Luck, Kai ^{[1
]}

Grecos, Christos ^{[3
]}

Wang, Qi ^{[4
]}

Vogt, Florian ^{[5
]}

机构：

[1] Hamburg Univ Appl Sci, Dept Informat, Hamburg, Germany

[2] Univ West Scotland, Engn & Comp, Glasgow, Lanark, Scotland

[3] Cent Washington Univ CWU, Comp Sci Dept, Ellensburg, WA USA

[4] Univ West Scotland, Sch Engn & Comp, Glasgow, Lanark, Scotland

[5] Hamburg Univ Appl Sci, Innovat Kontakt Stelle IKS Hamburg, Hamburg, Germany

来源：

10TH ACM INTERNATIONAL CONFERENCE ON PERVASIVE TECHNOLOGIES RELATED TO ASSISTIVE ENVIRONMENTS (PETRA 2017) | 2017年

关键词：

Affective Computing; Facial Expression Recognition; Benchmark; Application specific Clustering of Emotions;

D O I：

10.1145/3056540.3056546

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, we provide insights towards achieving more robust automatic facial expression recognition in smart environments based on our benchmark with three labeled facial expression databases. These databases are selected to test for desktop, 3D and smart environment application scenarios. This work is meant to provide a neutral comparison and guidelines for developers and researchers interested to integrate facial emotion recognition technologies in their applications, understand its limitations and adaptation as well as enhancement strategies. We also introduce and compare three different metrics for finding the primary expression in a time window of a displayed emotion. In addition, we outline facial emotion recognition limitations and enhancements for smart environments and non-frontal setups. By providing our comparison and enhancements we hope to build a bridge from affective computing research and solution providers to application developers that like to enhance new applications by including emotion based user modeling.

引用

页码：37 / 44

页数：8

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