High-Speed Video System for Micro-Expression Detection and Recognition
Micro-expressions play an essential part in understanding non-verbal communication and deceit detection. They are involuntary, brief facial movements that are shown when a person is trying to conceal something. Automatic analysis of micro-expression is challenging due to their low amplitude and to t...
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doaj-3d877987a4164e55bc15584848547b552020-11-24T21:08:42ZengMDPI AGSensors1424-82202017-12-011712291310.3390/s17122913s17122913High-Speed Video System for Micro-Expression Detection and RecognitionDiana Borza0Radu Danescu1Razvan Itu2Adrian Darabant3Computer Science Department, Technical University of Cluj-Napoca, 28 Memorandumului Street, 400114 Cluj Napoca, RomaniaComputer Science Department, Technical University of Cluj-Napoca, 28 Memorandumului Street, 400114 Cluj Napoca, RomaniaComputer Science Department, Technical University of Cluj-Napoca, 28 Memorandumului Street, 400114 Cluj Napoca, RomaniaComputer Science Department, Babes Bolyai University, 58-60 Teodor Mihali Street, C333, 400591 Cluj Napoca, RomaniaMicro-expressions play an essential part in understanding non-verbal communication and deceit detection. They are involuntary, brief facial movements that are shown when a person is trying to conceal something. Automatic analysis of micro-expression is challenging due to their low amplitude and to their short duration (they occur as fast as 1/15 to 1/25 of a second). We propose a fully micro-expression analysis system consisting of a high-speed image acquisition setup and a software framework which can detect the frames when the micro-expressions occurred as well as determine the type of the emerged expression. The detection and classification methods use fast and simple motion descriptors based on absolute image differences. The recognition module it only involves the computation of several 2D Gaussian probabilities. The software framework was tested on two publicly available high speed micro-expression databases and the whole system was used to acquire new data. The experiments we performed show that our solution outperforms state of the art works which use more complex and computationally intensive descriptors.https://www.mdpi.com/1424-8220/17/12/2913micro-expression spottingmicro-expression recognitionaffective computingfacial expression recognitiondifference images |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Diana Borza Radu Danescu Razvan Itu Adrian Darabant |
spellingShingle |
Diana Borza Radu Danescu Razvan Itu Adrian Darabant High-Speed Video System for Micro-Expression Detection and Recognition Sensors micro-expression spotting micro-expression recognition affective computing facial expression recognition difference images |
author_facet |
Diana Borza Radu Danescu Razvan Itu Adrian Darabant |
author_sort |
Diana Borza |
title |
High-Speed Video System for Micro-Expression Detection and Recognition |
title_short |
High-Speed Video System for Micro-Expression Detection and Recognition |
title_full |
High-Speed Video System for Micro-Expression Detection and Recognition |
title_fullStr |
High-Speed Video System for Micro-Expression Detection and Recognition |
title_full_unstemmed |
High-Speed Video System for Micro-Expression Detection and Recognition |
title_sort |
high-speed video system for micro-expression detection and recognition |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2017-12-01 |
description |
Micro-expressions play an essential part in understanding non-verbal communication and deceit detection. They are involuntary, brief facial movements that are shown when a person is trying to conceal something. Automatic analysis of micro-expression is challenging due to their low amplitude and to their short duration (they occur as fast as 1/15 to 1/25 of a second). We propose a fully micro-expression analysis system consisting of a high-speed image acquisition setup and a software framework which can detect the frames when the micro-expressions occurred as well as determine the type of the emerged expression. The detection and classification methods use fast and simple motion descriptors based on absolute image differences. The recognition module it only involves the computation of several 2D Gaussian probabilities. The software framework was tested on two publicly available high speed micro-expression databases and the whole system was used to acquire new data. The experiments we performed show that our solution outperforms state of the art works which use more complex and computationally intensive descriptors. |
topic |
micro-expression spotting micro-expression recognition affective computing facial expression recognition difference images |
url |
https://www.mdpi.com/1424-8220/17/12/2913 |
work_keys_str_mv |
AT dianaborza highspeedvideosystemformicroexpressiondetectionandrecognition AT radudanescu highspeedvideosystemformicroexpressiondetectionandrecognition AT razvanitu highspeedvideosystemformicroexpressiondetectionandrecognition AT adriandarabant highspeedvideosystemformicroexpressiondetectionandrecognition |
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