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Towards Real-Life Facial Expression Recognition SystemsBENTA, K.-I. , VAIDA, M.-F.
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facial expression recognition, affective computing, feature extraction, classification, database
recognition(74), facial(70), computing(20), pattern(19), emotion(16), analysis(15), automatic(14), affective(14), image(12), vision(10)
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About this article
Date of Publication: 2015-05-31
Volume 15, Issue 2, Year 2015, On page(s): 93 - 102
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2015.02012
Web of Science Accession Number: 000356808900012
SCOPUS ID: 84979726417
Facial expressions are a set of symbols of great importance for human-to-human communication. Spontaneous in their nature, diverse and personal, facial expressions demand for real-time, complex, robust and adaptable facial expression recognition (FER) systems to facilitate the human-computer interaction. The last years' research efforts in the recognition of facial expressions are preparing FER systems to step into the real-life. In order to meet the before-mentioned requirements, this article surveys the work in FER since 2008, particularly adopting the discrete states emotion model in a quest for the most valuable FER works/systems. We first present the new spontaneous facial expression databases and then organize the real-time FER solutions grouped by spontaneous and posed facial expression databases. Then automatic FERs are compared and the cross-database validation method is presented. Finally, we outline FER system open issues to meet real-life challenges.
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 Real-Time Facial Emotion Recognition Framework for Employees of Organizations Using Raspberry-Pi, Rathour, Navjot, Khanam, Zeba, Gehlot, Anita, Singh, Rajesh, Rashid, Mamoon, AlGhamdi, Ahmed Saeed, Alshamrani, Sultan S., Applied Sciences, ISSN 2076-3417, Issue 22, Volume 11, 2021.
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 Anatomization of the systems of dimension relaxation for facial recognition, Raha, Mayamin Hamid, Deb, Tonmoay, Rahmun, Mahieyin, Chen, Tim, Intelligent Decision Technologies, ISSN 1872-4981, Issue 4, Volume 14, 2021.
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 Mining Inconsistent Emotion Recognition Results With the Multidimensional Model, Landowska, Agnieszka, Zawadzka, Teresa, Zawadzki, Michal, IEEE Access, ISSN 2169-3536, Issue , 2022.
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 Software Architecture Design for Spatially-Indexed Media in Smart Environments, SCHIPOR, O.-A., WU, W., TSAI, W.-T., VATAVU, R.-D., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 2, Volume 17, 2017.
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 The current challenges of automatic recognition of facial expressions: A systematic review, Masson, Audrey, Cazenave, Guillaume, Trombini, Julien, Batt, Martine, AI Communications, ISSN 1875-8452, Issue 3-6, Volume 33, 2020.
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 Comparison of selected off-the-shelf solutions for emotion recognition based on facial expressions, Brodny, Grzegorz, Kolakowska, Agata, Landowska, Agnieszka, Szwoch, Mariusz, Szwoch, Wioleta, Wrobel, Michal R., 2016 9th International Conference on Human System Interactions (HSI), ISBN 978-1-5090-1729-4, 2016.
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 A multimodal affective monitoring tool for mobile learning, Benta, Kuderna-Iulian, Cremene, Marcel, Vaida, Mircea-Florin, 2015 14th RoEduNet International Conference - Networking in Education and Research (RoEduNet NER), ISBN 978-1-4673-8179-6, 2015.
Digital Object Identifier: 10.1109/RoEduNet.2015.7311824 [CrossRef]
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
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