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Journal : TELKOMNIKA (Telecommunication Computing Electronics and Control)

Facial expression recognition of 3D image using facial action coding system (FACS) Hardianto Wibowo; Fachrunnisa Firdausi; Wildan Suharso; Wahyu Andhyka Kusuma; Dani Harmanto
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 2: April 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i2.9304

Abstract

Facial expression or mimic is one of the results of muscle motion on the face. In a large Indonesian dictionary, the expression is a disclosure or process of declaring, i.e. showing or expressing intentions, ideas of feelings and so on. Facial expression is affected by the cranial nerve VII or Nervus Facialis. In research conducted Paul Ekman got a standardization of expression in the format of a movement called the Facial Action Coding System (FACS). In his research, Paul Ekman said six basic expressions of happiness, sadness, shock, fear, anger, and disgust. In muscle anatomy, that every moving muscle must be contraction, and in the event of contraction, the muscle will expand or swell. Muscles are divided into three parts of origo and insersio as the tip of muscle and belli as the midpoint of the muscle, so any movement occurs then the muscle part belli will expand or swell. Data retrieval technique that is by recording data in 3D, any contraction occurs then the belli part of the muscle will swell and this data will be processed and compared. From this data processing will be obtained the maximum strength of contraction that will be used as a reference for the magnitude of expression made by the model. In the detection of expression is ecluidience distance by comparing the initial data with movement data. The result of this research is a detection of expression and the amount of expression that occurs. A conclusion of this research, we can reconstruction of facial expression detection using FACS, for the example the happiness expression using AU 6 and AU 12 and in this research AU 6 and AU 12 in area 1 and area 4, and in this area it so higher than the other.
Human activity recognition for static and dynamic activity using convolutional neural network Agus Eko Minarno; Wahyu Andhyka Kusuma; Yoga Anggi Kurniawan
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 6: December 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i6.20994

Abstract

Evaluated activity as a detail of the human physical movement has become a leading subject for researchers. Activity recognition application is utilized in several areas, such as living, health, game, medical, rehabilitation, and other smart home system applications. An accelerometer was popular sensors to recognize the activity, as well as a gyroscope, which can be embedded in a smartphone. Signal was generated from the accelerometer as a time-series data is an actual approach like a human actifvity pattern. Motion data have acquired in 30 volunteers. Dynamic actives (walking, walking upstairs, walking downstairs) as DA and static actives (laying, standing, sitting) as SA were collected from volunteers. SA and DA it's a challenging problem with the different signal patterns, SA signals coincide between activities but with a clear threshold, otherwise the DA signal is clearly distributed but with an adjacent upper threshold. The proposed network structure achieves a significant performance with the best overall accuracy of 97%. The result indicated the ability of the model for human activity recognition purposes.
Co-Authors Abi Maulana Aditya Nugroho Admodisastro, Novia Indriaty Ageng Widjaya Saputra Agung Tri Adi Wicaksono Agus Eko Minarno Ahmad Alif Asy’ari Syukur Ahmad Hamdani Ahmad Raihan Djamarullah Akbi, Denar Regata Aldyth Sugiharto Wijaya Amalia Pradya Paramita Andika Surya Listya Yudhana Anggreani Tyas Sari Ani Tri Wahyuningsih Ari Firmanto Arif Rahman Hidayatullah Arindra Kurniawan Hadisurya Augie Winanda Favourite Azisz, Ahmad Miftahul AZMI, AZMI Azrul Hazri bin Jantan Bimo Gempar Buono binti Mohd Norowi, Noris Chandra Sebastian Dandung Satrio Wulang Jiwo Dani Harmanto Dara Sucia Decya Holygina Benita Decya Holygina Benita Diah Ayu Fitriani Eko Felix Nur Noftianto Evi Dwi Wahyuni Fachrunnisa Firdausi Fahmi BN Fuad Alamudi Fajar Maulideo Anthaqo Fauzan, Fauzan Fitriani, Diah Ayu Gifary, Maulana Alan Gita Indah Martasari Gita Indah Martasari, Gita Gita Indah Marthasari Haidar Rais Abdillah Halimi, Imam Hardianto Wibowo Haris Diyaul Fata Hariyady Hariyady Helda Yuliani Sari Helmi Ramadhan Hendra Wijaya Heni Pujiastuti Ikhlassul Fauziah Amma Istiqomah, Istiqomah Jantan, Azrul Hazri Kenanga, Larynt Sawfa Kharisma Muzaki Ghufron Kresna Wahyu Ramadhani Lathifi, Andi Syahrial Luqman Hakim Mahar Faiqurahman MAKNUN, NUR EVINA Maryaeni Maryaeni Maulana F Aksan Mochamad Arifin Mochammad Inzaghi Hafizh Ikhsan Moh Ridwan Muchammad Romadhoni Muhammad Einggi Gusti Pratama Muhammad Shohib, Muhammad Muhammad Zulfan Faizal Nabillah Annisa Rahmayanti Naser Jawas, Naser Nia Dwi Nurul Safitri Norhabibah, Siti Noris binti Mohd Norowi Norowi, Noris Novia Indriaty Admodisastro Novia Komala Sari Noviasari, Vebrian Nur Ihsan, Abdul Jabbar Nuraini Saputri Oktaviani, Chintya Tria Diana Ovan Septian Prasetya, Rendy Wiranto Priyatna Budianto Rafiatul Husna Reikisyifa, Clarissa Sanindita Rellanti Diana Kristy rellanti diana kristy Restu Pranansha Anugerah Rizalwan Ardi Ramandita Roy Inzaqhi Saputra Rusli bin Abdullah S, Vinna Rahmayanti Sabrina Nurul Ubay Saleh, Abd. Salma Auliannisa Sari, Anggreani Tyas Sari, Zamah Sarlita Rizka Anggraeni Selma Osa Rohimah Siti Alfiyatun Ni’mah Siti Norhabibah Supriyanto Supriyanto Supriyanto Syahbana, Ahmad Fauzan Ali Syaifuddin Syaifuddin Syauqi Hidayatul Hakim Tuti Karen Tia Ubay, Sabrina Nurul Vebrian Noviasari Widya Rizka Ulul Fadilah Wildan Suharso Yasina Tisha Karina Yoga Anggi Kurniawan Yogha Arieka Adnantha Yuda Munarko Zamah Sari