Identifying Real and Posed Smiles from Observers’ Galvanic Skin Response and Blood Volume Pulse

Renshang Gao, Atiqul Islam, Tom Gedeon, Md Zakir Hossain*

*المؤلف المقابل لهذا العمل

نتاج البحث

3 اقتباسات (Scopus)

ملخص

This study addresses the question whether galvanic skin response (GSR) and blood volume pulse (BVP) of untrained and unaided observers can be used to identify real and posed smiles from different sets of smile videos or smile images. Observers were shown smile face videos/images, either singly or paired, with the intention to recognise each viewed as real or posed smiles. We created four experimental situations, namely single images (SI), single videos (SV), paired images (PI), and paired videos (PV). The GSR and BVP signals were recorded and processed. Our machine learning classifiers reached the highest accuracy of 93.3%, 87.6%, 92.0%, 91.7% for PV, PI, SV, and SI respectively. Finally, PV and SI were found to be the easiest and hardest way to identify real and posed smiles respectively. Overall, we demonstrated that observers’ subconscious physiological signals (GSR and BVP) are able to identify real and posed smiles at a good accuracy.

اللغة الأصليةEnglish
عنوان منشور المضيفNeural Information Processing - 27th International Conference, ICONIP 2020, Proceedings
المحررونHaiqin Yang, Kitsuchart Pasupa, Andrew Chi-Sing Leung, James T. Kwok, Jonathan H. Chan, Irwin King
ناشرSpringer Science and Business Media Deutschland GmbH
الصفحات375-386
عدد الصفحات12
رقم المعيار الدولي للكتب (المطبوع)9783030638290
المعرِّفات الرقمية للأشياء
حالة النشرPublished - 2020
الحدث27th International Conference on Neural Information Processing, ICONIP 2020 - Bangkok
المدة: نوفمبر ١٨ ٢٠٢٠نوفمبر ٢٢ ٢٠٢٠

سلسلة المنشورات

الاسمLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
مستوى الصوت12532 LNCS
رقم المعيار الدولي للدوريات (المطبوع)0302-9743
رقم المعيار الدولي للدوريات (الإلكتروني)1611-3349

Conference

Conference27th International Conference on Neural Information Processing, ICONIP 2020
الدولة/الإقليمThailand
المدينةBangkok
المدة١١/١٨/٢٠١١/٢٢/٢٠

ASJC Scopus subject areas

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