The Face of Trust: Using Facial Action Units (AUs) as Indicators of Trust in Automation

2021 ◽  
pp. 265-273
Author(s):  
Jonathan Soon Kiat Chua ◽  
Hong Xu ◽  
Sun Woh Lye
2020 ◽  
Vol 38 (11A) ◽  
pp. 1717-1729
Author(s):  
Sana A. Nasser ◽  
Ivan A. Hashim ◽  
Wissam H. Ali

Most psychologists believe that facial behavior through depression differs from facial behavior in the absence of depression, so facial behavior can be utilized as a dependable indicator for spotting depression. Visual depression diagnosis system (VDD) establishes dependents on expressions of the face that are expense-effective and movable. At this work, the VDD system is designed according to the Facial Action Coding System (FACS) to extract features of the face. The key concept of the Facial Action Coding System (FACS) to explain the whole face behavior utilizing Action Units (AUs), every AU is linked to the motion of unique or maybe further face muscles. Six AUs have utilized as depression features; those action units are AUs 4, 5, 6, 7, 10, and 12. The datasets that employed to evaluate the performance of the proposed system are gathered for 125 participants (30 males, 95 females); many of them are among 17-60 years of age. At the final step of the current system, four kinds of classification techniques were applied separately; those classifiers algorithms are KNN, SVM, PCA, and LDA. The outcomes of the simulation indicate that the best outcomes are achieved utilizing the KNN and LDA classifiers, where the success rate is 85%. New classification methods in the VDD system are the key contributions of this research, gather real databases that can utilize to compute the performance of every other VDD system based on face emotions, and choose appropriate features of the face.


2018 ◽  
Vol 9 (2) ◽  
pp. 31-38
Author(s):  
Fransisca Adis ◽  
Yohanes Merci Widiastomo

Facial expression is one of some aspects that can deliver story and character’s emotion in 3D animation. To achieve that, we need to plan the character facial from very beginning of the production. At early stage, the character designer need to think about the expression after theu done the character design. Rigger need to create a flexible rigging to achieve the design. Animator can get the clear picture how they animate the facial. Facial Action Coding System (FACS) that originally developed by Carl-Herman Hjortsjo and adopted by Paul Ekman and Wallace V. can be used to identify emotion in a person generally. This paper is going to explain how the Writer use FACS to help designing the facial expression in 3D characters. FACS will be used to determine the basic characteristic of basic shapes of the face when show emotions, while compare with actual face reference. Keywords: animation, facial expression, non-dialog


2021 ◽  
Author(s):  
Wenqiang Guo ◽  
Ziwei Xu ◽  
Zhigao Guo ◽  
Lingling Mao ◽  
Yongyan Hou ◽  
...  

Author(s):  
Manh Tu Vu ◽  
Marie Beurton-Aimar ◽  
Pierre-yves Dezaunay ◽  
Marine Cotty Eslous
Keyword(s):  

2010 ◽  
Vol 35 (1) ◽  
pp. 1-16 ◽  
Author(s):  
Etienne B. Roesch ◽  
Lucas Tamarit ◽  
Lionel Reveret ◽  
Didier Grandjean ◽  
David Sander ◽  
...  

2020 ◽  
Author(s):  
Andrew Langbehn ◽  
Dasha Yermol ◽  
Fangyun Zhao ◽  
Christopher Thorstenson ◽  
Paula Niedenthal

Abstract According to the familiar axiom, the eyes are the window to the soul. However, wearing masks to prevent the spread of COVID-19 involves occluding a large portion of the face. Do the eyes carry all of the information we need to perceive each other’s emotions? We addressed this question in two studies. In the first, 162 Amazon Mechanical Turk (MTurk) workers saw videos of human faces displaying expressions of happiness, disgust, anger, and surprise that were fully visible or covered by N95, surgical, or cloth masks and rated the extent to which the expressions conveyed each of the four emotions. Across mask conditions, participants perceived significantly lower levels of the expressed (target) emotion and this was particularly true for expressions composed of greater facial action in the lower part of the faces. Furthermore, higher levels of other (non-target) emotions were perceived in masked compared to visible faces. In the second study, 60 MTurk workers rated the extent to which three types of smiles (reward, affiliation, and dominance smiles), either visible or masked, conveyed positive feelings, reassurance, and superiority. They reported that masked smiles communicated less of the target signal than visible faces, but not more of other possible signals. Political attitudes were not systematically associated with disruptions in the processing of facial expression caused by masking the face.


Author(s):  
Reneiro Andal Virrey ◽  
Wahyu Caesarendra ◽  
Muhammad Iskandar bin Pg. Hj Petra ◽  
Emeroylariffion Abas ◽  
Asmah Husaini ◽  
...  

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