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Facial Expression Emotion Detection for Real-Time Embedded Systems

1
Department of Electronic and Computer Engineering, Brunel University London, Uxbridge UB8 3PH, UK
2
Department of Electronics and Multimedia Telecommunications, Technical University of Kosice, Letna 9, 04001 Kosice, Slovakia
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Author to whom correspondence should be addressed.
This paper is an extended version of our paper in Proceedings of Innovative Computing Technology (INTECH 2017), Luton, UK, 16–18 August 2017; with permission from IEEE.
Technologies 2018, 6(1), 17; https://doi.org/10.3390/technologies6010017
Received: 15 December 2017 / Revised: 13 January 2018 / Accepted: 22 January 2018 / Published: 26 January 2018
Recently, real-time facial expression recognition has attracted more and more research. In this study, an automatic facial expression real-time system was built and tested. Firstly, the system and model were designed and tested on a MATLAB environment followed by a MATLAB Simulink environment that is capable of recognizing continuous facial expressions in real-time with a rate of 1 frame per second and that is implemented on a desktop PC. They have been evaluated in a public dataset, and the experimental results were promising. The dataset and labels used in this study were made from videos, which were recorded twice from five participants while watching a video. Secondly, in order to implement in real-time at a faster frame rate, the facial expression recognition system was built on the field-programmable gate array (FPGA). The camera sensor used in this work was a Digilent VmodCAM — stereo camera module. The model was built on the Atlys™ Spartan-6 FPGA development board. It can continuously perform emotional state recognition in real-time at a frame rate of 30. A graphical user interface was designed to display the participant’s video in real-time and two-dimensional predict labels of the emotion at the same time. View Full-Text
Keywords: FPGA; facial expression analysis; artificial intelligence; real-time implementation FPGA; facial expression analysis; artificial intelligence; real-time implementation
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Turabzadeh, S.; Meng, H.; Swash, R.M.; Pleva, M.; Juhar, J. Facial Expression Emotion Detection for Real-Time Embedded Systems. Technologies 2018, 6, 17.

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