Menuju Pengenalan Ekspresi Mikro: Pendeteksian Komponen Wajah Menggunakan Discriminative Response Map Fitting

The observations made in the study of micro-expression are to recognize and track the very subtle movements of certain facial areas and in a short time. In this study, the observation of movement is held in some areas of the face component. The facial and facial components detection is the pre-proce...

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Main Authors: Ulla Delfana Rosiani, Priska Choirina, Surya Sumpeno, Mauridhy Hery P.
Format: Article
Language:English
Published: Universitas Gadjah Mada 2018-06-01
Series:Jurnal Nasional Teknik Elektro dan Teknologi Informasi
Subjects:
Online Access:http://ejnteti.jteti.ugm.ac.id/index.php/JNTETI/article/view/424
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spelling doaj-d1a220a074e4476293ed614e21bf28452020-11-25T00:07:13ZengUniversitas Gadjah MadaJurnal Nasional Teknik Elektro dan Teknologi Informasi2301-41562460-57192018-06-017110.22146/jnteti.v7i2.424356Menuju Pengenalan Ekspresi Mikro: Pendeteksian Komponen Wajah Menggunakan Discriminative Response Map FittingUlla Delfana RosianiPriska ChoirinaSurya SumpenoMauridhy Hery P.The observations made in the study of micro-expression are to recognize and track the very subtle movements of certain facial areas and in a short time. In this study, the observation of movement is held in some areas of the face component. The facial and facial components detection is the pre-process stage on micro-expression recognition system. The goal at this stage is to get face and face components accurately and quickly on every movement of the video sequence or image sequence. The face landmark point of the Discriminative Response Map Fitting (DRMF) method can be used to get face components area accurately and quickly. This can be done because the facial landmark points used in this model-based method do not change when objects are moved, rotated, or scaled. The results obtained by using this method are accurate with a 100% accuracy value compared to the Haar Cascade Classifier method with an average accuracy of 44%. In addition, the average time required in the formation of facial component boxes for each frame is 0.08 seconds, faster than the Haar Cascade Classifier method of 0.32 seconds. With the results obtained, then the detection of facial components can be obtained accurately and quickly. Furthermore, the boxes of face components obtained are expected to display the appropriate data to be processed correctly and accurately in the next stage, feature extraction and the classification of micro-expression motion stage.http://ejnteti.jteti.ugm.ac.id/index.php/JNTETI/article/view/424deteksi komponen wajah, DRMF, titik landmark wajah, ekspresi mikro
collection DOAJ
language English
format Article
sources DOAJ
author Ulla Delfana Rosiani
Priska Choirina
Surya Sumpeno
Mauridhy Hery P.
spellingShingle Ulla Delfana Rosiani
Priska Choirina
Surya Sumpeno
Mauridhy Hery P.
Menuju Pengenalan Ekspresi Mikro: Pendeteksian Komponen Wajah Menggunakan Discriminative Response Map Fitting
Jurnal Nasional Teknik Elektro dan Teknologi Informasi
deteksi komponen wajah, DRMF, titik landmark wajah, ekspresi mikro
author_facet Ulla Delfana Rosiani
Priska Choirina
Surya Sumpeno
Mauridhy Hery P.
author_sort Ulla Delfana Rosiani
title Menuju Pengenalan Ekspresi Mikro: Pendeteksian Komponen Wajah Menggunakan Discriminative Response Map Fitting
title_short Menuju Pengenalan Ekspresi Mikro: Pendeteksian Komponen Wajah Menggunakan Discriminative Response Map Fitting
title_full Menuju Pengenalan Ekspresi Mikro: Pendeteksian Komponen Wajah Menggunakan Discriminative Response Map Fitting
title_fullStr Menuju Pengenalan Ekspresi Mikro: Pendeteksian Komponen Wajah Menggunakan Discriminative Response Map Fitting
title_full_unstemmed Menuju Pengenalan Ekspresi Mikro: Pendeteksian Komponen Wajah Menggunakan Discriminative Response Map Fitting
title_sort menuju pengenalan ekspresi mikro: pendeteksian komponen wajah menggunakan discriminative response map fitting
publisher Universitas Gadjah Mada
series Jurnal Nasional Teknik Elektro dan Teknologi Informasi
issn 2301-4156
2460-5719
publishDate 2018-06-01
description The observations made in the study of micro-expression are to recognize and track the very subtle movements of certain facial areas and in a short time. In this study, the observation of movement is held in some areas of the face component. The facial and facial components detection is the pre-process stage on micro-expression recognition system. The goal at this stage is to get face and face components accurately and quickly on every movement of the video sequence or image sequence. The face landmark point of the Discriminative Response Map Fitting (DRMF) method can be used to get face components area accurately and quickly. This can be done because the facial landmark points used in this model-based method do not change when objects are moved, rotated, or scaled. The results obtained by using this method are accurate with a 100% accuracy value compared to the Haar Cascade Classifier method with an average accuracy of 44%. In addition, the average time required in the formation of facial component boxes for each frame is 0.08 seconds, faster than the Haar Cascade Classifier method of 0.32 seconds. With the results obtained, then the detection of facial components can be obtained accurately and quickly. Furthermore, the boxes of face components obtained are expected to display the appropriate data to be processed correctly and accurately in the next stage, feature extraction and the classification of micro-expression motion stage.
topic deteksi komponen wajah, DRMF, titik landmark wajah, ekspresi mikro
url http://ejnteti.jteti.ugm.ac.id/index.php/JNTETI/article/view/424
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