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Choirina, Priska
Universitas Islam Raden Rahmat
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Journal : Jurnal Nasional Teknik Elektro dan Teknologi Informasi

 1 
Menuju Pengenalan Ekspresi Mikro: Pendeteksian Komponen Wajah Menggunakan Discriminative Response Map Fitting Ulla Delfana Rosiani; Priska Choirina; Surya Sumpeno; Mauridhi Hery Purnomo
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 7 No 2: Mei 2018
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1573.841 KB)

Abstract

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.
Perbandingan Fase Ekspresi Menggunakan Local Binary Pattern Histogram Untuk Pengenalan Ekspresi Mikro Ulla Delfana Rosiani; Priska Choirina; Yessy Nindi Pratiwi Pratiwi; Septiar Enggar Sukmana
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 12 No 4: November 2023
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v12i4.7818

Abstract

Microexpression is an emotional representation occurring spontaneously and cannot be controlled consciously. It is temporary (short duration) with subtle movements, making it difficult to detect with the naked eye. Microexpressions’ muscle movements are generated in only a few small areas of the face, so observation of specific areas results in faster computation time and provides important information compared to observation of the entire face. This research proposes reducing the observation area and phase for microexpression recognition. The observed areas in the Chinese Academy of Science Micro-Expressions (CASME II) dataset are left and right eyebrows, right and left eyes, and mouth. The observation phase of microexpressions included analyzing the comparison in the onset to offset phase (“fullOAO”) and in the onset, apex, and offset phase (“OAO”). Feature extraction was performed using a simple local binary patterns histogram (LBPH) method, which can represent local features in the facial area. The best result of the proposed method was the “fullOAO” phase with an accuracy of 96.8% (using support vector machine-radial basis function, SVM-RBF) and an average computation time of 0.192 ms per frame and 10.473 ms per video. In “OAO” phase type, an accuracy of 87.7% was achieved with a computation time of 0.159 ms per frame and 0.576 ms per video. The difference in accuracy and computation time between the two-phase types occurs because the number of frames in “fullOAO” type is greater than in “OAO”, resulting in a different amount of processing time and feature extraction data. However, the 9% decrease in accuracy does not significantly affect the accuracy since the accuracy rate is still relatively good, above 80%. Furthermore, the correct measurement for computation time was the time taken to process each frame in the input video. Therefore, the proposed method can produce fast computation time and relatively accurate recognition.
Co-Authors Ahmad Mukhlis Ahmad Rifa’i Ahmad Saepuddin Ainun Nikmah Akbar, Fasal Alfadani, Fikri Alfi Fadliana Andjani, Bella Sita Anggraeni Hadi Pratiwi Arga Yoda, Vincensius Arsistawa, Firmanda Ahmadani Ashar, Imam Asshidiqi, Faisol Khoufi Atika Prasetyawati Bagus Seta Bagus Seta Inba Cipta Baqi, Rijalul Bella Cornelia Tjiptady Bella Sita Andjani Bila Nastiti Tasaufi Candra Pradhana Chanda, Muhammad Rizki Cipta, Bagus Seta Inba Darajad, Pangestuti Prima Erlillah Rizqi Kusuma Pradani Fahmi, Muhammad Hanif Farchan Aziz Farhan Farid Wahyudi Farid Wahyudi Febriana, Kiki Dwi Fitriani, Indah Martha Fitriani, Indah Martha Hamzah Haz, Dul Bazir Humam, Muhammad Na im Inba Cipta, Bagus Seta Jeki Saputra Kumala, Tri Ayu Tirta Lia Damayanti M. Rizal Akbar Zam Zami Marthen, Verdison Mauridhi Hery Purnomo Mochamad Luthfi Nazif Suryana Mochamad Sulaiman Moh Fajar Alfan Rezaky Mojibur Rohman Mufti, Muhammad Nabil Muhamat Maariful Huda Muhammad Rizki Chanda Muhammat Maariful Huda Novia Ratnasari Nurcahyo, Alvin PANGESTUTI PRIMA DARAJAT Prasetyawati, Atika Pratiwi, Anggraeni Hadi Purwatiningsih Purwatiningsih Putra Prima Arhandi, Putra Prima Rahmah Nur Azizah Zain Rahman, Mojibur Rahmawati, Zurriat Nyndia Raka Anugrah Hamdhana Rijalul Baqi Rizqi Darma Rusdiyan Yusron Rohman, Mojibur Rosa Andrie Asmara Rosiani, Ulla Delfana Satria Utama Septarina, Amalia Agung Septiar Enggar Sukmana Surya Sumpeno Tarecha, Rachmad Imam Tasaufi, Bila Nastiti Tjiptady, Bella Cornelia Ulla Delfana Rosiani Ulla Delfana Rosiani Urnika Mudhifatul Urnika Mudhifatul Jannah Urnika Mudhifatul Jannah Urnika Mudhifatul Jannah, Urnika Mudhifatul Wahyu Pambudi Wahyudi, Farid widaningrum, anisa hudi Widyantoro, Bagas Wijaya, Muhammad Adi Yayi Febdia Pradani Yessy Nindi Pratiwi Pratiwi Yudhi Darmawan Yuliono, Gun