• Journal of Acupuncture Research
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• 제33권3호
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• pp.89-99
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• 2016

Objectives : This study was performed to develop objective methods for evaluating facial palsy sequelae using a 3D Facial Scanning System. Methods : Fifty-eight patients with facial palsy sequelae were selected. Their medical records were reviewed to collect demographic data, facial palsy sequelae evaluation, Facial Disability Index questionnaire, and test results (3D Facial Scanning System). Five different facial expressions (at rest, eye closure, eyebrow elevation, smiling, and whistling) were photographed. Sunnybrook Scale was associated with distances between predetermined facial points. Results : The average Sunnybrook composite score was $58.88{\pm}17.31$. Secondary movements (mouth to eye synkinesis, contracture of eye, and contracture of mouth) showed significant difference according to the Sunnybrook Scale. In voluntary movements, eyebrow height at eyebrow elevation, length between mouth angle and central line while whistling, and eyelid width at maximum eye opening showed significant difference. Facial palsy Sequelae Index (FSI) was correlated with Sunnybrook sub-scales (resting symmetry, voluntary movement, and synkinesis). Conclusion : These results demonstrate that a 3D Facial Scanning System is useful for evaluating facial palsy sequelae. This method may facilitate objective evaluation for facial palsy sequelae and it could be applied in clinical trials.

• 인지과학
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• 제6권2호
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• pp.47-79
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• 1995

오래 전부터 컴퓨터 그래픽을 이용한 얼굴의 표정 생성은 여러 분야에서 응용되어 왔고,요즘에는 가상현실감 분야나 원격 회의 분야 등에서 가상 에이전트의 표정을 생성하는데 사용되고 있다.그러나 네트워크를 통해 다중 참여자가 상호 작용을 하는 상황에서 표정을 생성하는 경우에는 상호작용을 위해 전송되어야 할 정보의 양으로 인해,실시간에 원하는 표정을 생성하기 어려운 경우가 생긴다.본 연구에서는 이러한 문지를 해결하기 위해 표정 생성에 Level-of-Detail을 적용하였다.Level-of-Detail은 그래픽스 분야에서 복잡한 물체의 외형을 좀 더 효율적으로 나타내기 위해 오랜 전부터 연구되어져 온 기법이지만 아직까지 표정 생성에 적용된 예는 없다.본 연구에서는 상황을 고려하여 적절하게 상세도를 변경하여 표정을 생성하도록 Level-of-Detail기법을 적용하는 방법에 대해 연구하였다.구현된 시스템은 텍스트,음성,Gui, 사용자의 머리의 움직임 등과 같은 다양한 입력에 대해 입모양과 동기화 되는 표정을 생성한다.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• 제29권4호
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• pp.150-160
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• 2018

Objectives: This study investigated the effect of social skills training (SST) on facial emotion recognition and discrimination in children with attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). Methods: Twenty-three children aged 7 to 10 years participated in our SST. They included 15 children diagnosed with ADHD and 8 with ASD. The participants' parents completed the Korean version of the Child Behavior Checklist (K-CBCL), the ADHD Rating Scale, and Conner's Scale at baseline and post-treatment. The participants completed the Korean Wechsler Intelligence Scale for Children-IV (K-WISC-IV) and the Advanced Test of Attention at baseline and the Penn Emotion Recognition and Discrimination Task at baseline and post-treatment. Results: No significant changes in facial emotion recognition and discrimination occurred in either group before and after SST. However, when controlling for the processing speed of K-WISC and the social subscale of K-CBCL, the ADHD group showed more improvement in total (p=0.049), female (p=0.039), sad (p=0.002), mild (p=0.015), female extreme (p=0.005), male mild (p=0.038), and Caucasian (p=0.004) facial expressions than did the ASD group. Conclusion: SST improved facial expression recognition for children with ADHD more effectively than it did for children with ASD, in whom additional training to help emotion recognition and discrimination is needed.

• Imaging Science in Dentistry
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• 제51권3호
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• pp.279-290
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• 2021

Purpose: Using images in the facial image comparison process poses a challenge for forensic experts due to limitations such as the presence of facial expressions. The aims of this study were to analyze how morphometric changes in the face during a spontaneous smile influence the facial image comparison process and to evaluate the reproducibility of measurements obtained by digital stereophotogrammetry in these situations. Materials and Methods: Three examiners used digital stereophotogrammetry to obtain 3-dimensional images of the faces of 10 female participants(aged between 23 and 45 years). Photographs of the participants' faces were captured with their faces at rest (group 1) and with a spontaneous smile (group 2), resulting in a total of 60 3-dimensional images. The digital stereophotogrammetry device obtained the images with a 3.5-ms capture time, which prevented undesirable movements of the participants. Linear measurements between facial landmarks were made, in units of millimeters, and the data were subjected to multivariate and univariate statistical analyses using Pirouette^® version 4.5 (InfoMetrix Inc., Woodinville, WA, USA) and Microsoft Excel^® (Microsoft Corp., Redmond, WA, USA), respectively. Results: The measurements that most strongly influenced the separation of the groups were related to the labial/buccal region. In general, the data showed low standard deviations, which differed by less than 10% from the measured mean values, demonstrating that the digital stereophotogrammetry technique was reproducible. Conclusion: The impact of spontaneous smiles on the facial image comparison process should be considered, and digital stereophotogrammetry provided good reproducibility.

• 감성과학
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• 제22권2호
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• pp.37-48
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• 2019

본 연구의 목적은 최근 심리구성주의 정서이론에서 제안한 얼굴정서 지각 과정에 미치는 언어의 영향을 정신물리학적 방법을 사용하여 검증하는 것이다. 본 연구에서는 감정단어가 얼굴표정 전에 제시될 경우, 얼굴표정의 정서 범주에 대한 판단 기준을 그 감정단어가 표상하는 정서 개념 맥락에 가깝게 이동시킬 것이라는 가설을 세웠다. 실험에서는 분노 또는 기쁨을 표현하는 감정단어가 표적 얼굴 전에 잠시 제시되었고, 표적 얼굴로는 중립에서 분노 (실험 1), 중립에서 행복 (실험 2)으로 점진적으로 변화하는 얼굴표정 중 하나가 무선적으로 제시되었다. 실험참가자는 표적얼굴의 정서를 분노 혹은 중립 (실험 1), 행복 혹은 중립 (실험 2)으로 판단하는 2안 강제선택 과제를 수행하였다. 실험 1 결과, 통제조건과 비교하여 분노 표현 감정단어들은 표적 얼굴정서를 분노로 판단하는 판단 경계 (PSE: the point of subjective equality)를 낮추었고, 행복 표현 감정단어들은 판단 경계를 높였다. 중립-행복 표정을 판단하는 실험 2에서는 반대의 결과가 관찰되었다. 본 연구의 결과는 얼굴정서를 지각하는 과정이 다양한 맥락 정보를 사용하여 능동적으로 구성하는 과정이며, 감정단어들은 정서에 대한 개념적 맥락을 제공함으로써 얼굴정서 지각에 영향을 준다는 구성된 정서 이론의 주장을 지지하는 것으로 해석할 수 있다.

• 한국문헌정보학회지
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• 제48권1호
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• pp.53-73
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• 2014

감정기반 컴퓨팅 환경의 발전에 따라서 이미지를 포함한 멀티미디어 정보 자원의 감정 접근과 이용은 중요한 연구과제이다. 본 연구는 이미지의 감정색인을 위한 시각적인 요인의 탐색적 규명을 목적으로 한다. 연구목적을 성취하기 위해서 본 연구는 사랑, 행복, 슬픔, 공포, 분노의 5가지 기본감정으로 색인된 15건의 이미지를 대상으로 20명의 연구 참여자와의 인터뷰를 통해서 총 620건의 감정 시각적 요인을 추출하였다. 감정을 촉발하는 시각적 요인(5가지)과 하위 요인(18가지)의 분포와 5가지 감정별 시각적 요인 분포를 분석하여 그 결과를 제시하였다. 이미지의 감정을 인지하는 주요한 시각적 요인으로는 얼굴표정, 인물의 동작이나 행위, 선, 형태, 크기 등의 조형적 요소가 차지하는 비중이 높은 것으로 나타났다. 개별 감정과 시각적인 요인과의 관계를 살펴보면, 사랑 감정은 인물의 동작이나 행위와 밀접하게 나타났으며, 행복 감정은 인물의 얼굴표정이 중요한 것으로 나타났다. 슬픔 감정 역시 인물의 동작이나 행위와 밀접하게 연계되어 있으며, 공포 감정은 얼굴의 표정과 깊은 관계가 있다. 분노 감정은 조형적인 요소인 선, 형태, 크기가 특징적으로 나타났다. 이러한 결과는 이미지가 지니는 내용기반 요소와 개념기반 요소의 복합적인 접근이 효과적인 감정색인에 있어서 중요하다는 것을 제시한다.

• 한국컴퓨터정보학회논문지
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• 제23권8호
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• pp.37-43
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• 2018

In this paper, we propose a framework that automatically suggests emotion using emotion analysis method based on facial expression change. We use Microsoft's Emotion API to calculate and analyze emotion values in facial expressions to recognize emotions that change over time. In this step, we use standard deviations based on peak analysis to measure and classify emotional changes. The difference between the classified emotion and the normal emotion is calculated, and the difference is used to recognize the emotion abnormality. We match user's emotions to relatively relaxed emotions using histograms and emotional meshes. As a result, we provide relaxed emotions to users through images. The proposed framework helps users to recognize emotional changes easily and to train their emotions through emotional relaxation.

• 한국멀티미디어학회논문지
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• 제21권8호
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• pp.917-924
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• 2018

Recently, researches using LBP and SVM have been performed as one of the image - based methods for facial emotion recognition. LBP, introduced by Ojala et al., is widely used in the field of image recognition due to its high discrimination of objects, robustness to illumination change, and simple operation. In addition, CS(Center-Symmetric)-LBP was used as a modified form of LBP, which is widely used for face recognition. In this paper, we propose a method to detect four facial expressions such as expressionless, happiness, surprise, and anger using deep neural network. The validity of the proposed method is verified using accuracy. Based on the existing LBP feature parameters, it was confirmed that the method using the deep neural network is superior to the method using the Adaboost and SVM classifier.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1988년도 추계학술대회 논문집 학회본부
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• pp.477-480
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• 1988

A new image coding system called knowledge- based coding is presented which uses positively the knowledge for coding objects. The 3- dimensional model and the psychological knowledge for a person's face can be used as the knowledge for a coding system, when a person's face is coding object. A transmitter analyzes input images and a receiver synthesizes output images using them. The construction of 3-dimensional model and the introduction of the psychological knowledge to the new coding system are discussed. The basic facial expressions are synthesized from a neutral face using them. The synthesized images are very natural.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2008년도 하계종합학술대회
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• pp.1015-1016
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• 2008

In this paper, the method which searchs a character of face and transforms it by FACS(Facial Action Coding System) for face modeling is suggested. FACS has a function to build an expression of face to AUs(Action Units) and make various face expressions. The system performs to find accurate Action Units of sample face and use setted AUs. Consequently it carries out the coefficient for transforming face model by 2D AUs matching.