• The KIPS Transactions:PartB
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• v.16B no.5
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• pp.395-402
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• 2009

This paper proposes an approach of a novel facial expression recognition to deal with different intensities to improve a performance of a facial expression recognition. Various expressions and intensities of each person make an affect to decrease the performance of the facial expression recognition. The effect of different intensities of facial expression has been seldom focused on. In this paper, a face expression template and an expression-intensity distribution model are introduced to recognize different facial expression intensities. These techniques, facial expression template and expression-intensity distribution model contribute to improve the performance of facial expression recognition by describing how the shift between multiple interest points in the vicinity of facial parts and facial parts varies for different facial expressions and its intensities. The proposed method has the distinct advantage that facial expression recognition with different intensities can be very easily performed with a simple calibration on video sequences as well as still images. Experimental results show a robustness that the method can recognize facial expression with weak intensities.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.04a
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• pp.265-268
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• 2002

얼굴은 성별, 나이, 인종에 따라 다양한 특징을 가지고 있어서 개개인을 구별하기가 쉽고 내적인 상태를 쉽게 볼 수 있는 중요한 도구로 여겨지고 있다. 본 논문은 얼굴표정 애니메이션을 위한 효과적인 방법으로 실제얼굴의 피부조직 얼굴 근육 등 해부학적 구조에 기반한 근육기반모델링을 이용하는 방법을 소개하고자 한다. 제안하는 시스템의 구성은 얼굴 와이어프레임 구성과 폴리곤 메쉬분할 단계, 얼굴에 필요한 근육을 적용시키는 단계, 근육의 움직임에 따른 얼굴 표정생성단계로 이루어진다. 와이어프레임 구성과 폴리곤 메쉬 분할 단계에서는 얼굴모델을 Water[1]가 제안한 얼굴을 기반으로 하였고, 하나의 폴리곤 메쉬를 4등분으로 분할하여 부드러운 3D 얼굴모델을 보여준다. 다음 단계는 얼굴 표정생성에 필요한 근육을 30 개로 만들어 실제로 표정을 지을 때 많이 쓰는 부위에 적용시킨다. 그 다음으로 표정생성단계는 FACS 에서 제안한 Action Unit 을 조합하고 얼굴표정에 따라 필요한 근육의 강도를 조절하여 더 자연스럽고 실제감 있는 얼굴표정 애니메이션을 보여준다.

• Science of Emotion and Sensibility
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• v.11 no.1
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• pp.11-21
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• 2008

This study was designed to examine the effect of depressive mood on identification of emotional facial expression. Participants were screened out of 305 college students on the basis of the BDI-II score. Students with BDI-II score higher than 14(upper 20%) were selected for the Depression Group and those with BDI-II score lower than 5(lower 20%) were selected for the Control Group. A final sample of 20 students in the Depression Group and 20 in the Control Group were presented with facial expression stimuli of an increasing degree of emotional intensity, slowly changing from a neutral to a full intensity of happy, sad, angry, or fearful expressions. The result showed that there was the significant interaction of Group by Emotion(esp. happy and sad) which suggested that depressive mood affects processing of emotional stimuli such as facial expressions. Implication of this result for mood-congruent information processing were discussed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.11a
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• pp.416-419
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• 1999

We Present a technique for recognizing facial expressions from image sequences. The technique uses muscle-based feature models for tracking facial features. Since the feature models are constructed with a small number of parameters and are deformable in the limited range and directions, each search space for a feature can be limited. The technique estimates muscular contractile degrees for classifying six principal facial express expressions. The contractile vectors are obtained from the deformations of facial muscle models. Similarities are defined between those vectors and representative vectors of principal expressions and are used for determining facial expressions.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.444-446
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• 2011

본 논문은 실시간으로 카메라 영상으로부터 얼굴의 각 특징점을 검출하고, 검출된 특징점을 이용하여 웃음 표정을 인식하는 시스템을 제안한다. 제안된 시스템은 ASM(Active Shape Model)을 이용하여 실시간 검출부에서 얼굴 영상을 획득한 다음 ASM 학습부에서 학습된 결과를 가지고 얼굴의 특징을 찾는다. 얼굴 특징의 영상으로부터 입술 영역을 검출한다. 이렇게 검출된 입술 영역과 얼굴 특징점을 이용하여 사용자의 웃음 표정을 검출하고 인식하는 방법을 사용함으로써 웃음 표정 인식의 정확도를 높힐 수 있음을 알 수 있었다.

• The KIPS Transactions:PartA
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• v.11A no.5
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• pp.383-390
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• 2004

This paper propose a method that controls facial expression of 3D avatar by having the user select a sequence of facial expressions in the space of facial expressions. And we setup its system. The space of expression is created from about 2400 frames consist of motion captured data of facial expressions. To represent the state of each expression, we use the distance matrix that represents the distances between pairs of feature points on the face. The set of distance matrices is used as the space of expressions. But this space is not such a space where one state can go to another state via the straight trajectory between them. We derive trajectories between two states from the captured set of expressions in an approximate manner. First, two states are regarded adjacent if the distance between their distance matrices is below a given threshold. Any two states are considered to have a trajectory between them If there is a sequence of adjacent states between them. It is assumed . that one states goes to another state via the shortest trajectory between them. The shortest trajectories are found by dynamic programming. The space of facial expressions, as the set of distance matrices, is multidimensional. Facial expression of 3D avatar Is controled in real time as the user navigates the space. To help this process, we visualized the space of expressions in 2D space by using the multidimensional scaling(MDS). To see how effective this system is, we had users control facial expressions of 3D avatar by using the system. As a result of that, users estimate that system is very useful to control facial expression of 3D avatar in real-time.

• Journal of the Korea Society of Computer and Information
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• v.15 no.4
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• pp.47-55
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• 2010

In this paper, we proposed a recognition system of smile facial expression for smile treatment training. The proposed system detects face candidate regions by using Haar-like features from camera images. After that, it verifies if the detected face candidate region is a face or non-face by using SVM(Support Vector Machine) classification. For the detected face image, it applies illumination normalization based on histogram matching in order to minimize the effect of illumination change. In the facial expression recognition step, it computes facial feature vector by using PCA(Principal Component Analysis) and recognizes smile expression by using a multilayer perceptron artificial network. The proposed system let the user train smile expression by recognizing the user's smile expression in real-time and displaying the amount of smile expression. Experimental result show that the proposed system improve the correct recognition rate by using face region verification based on SVM and using illumination normalization based on histogram matching.

• Korean Journal of Cognitive Science
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• v.18 no.1
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• pp.57-68
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• 2007

This study explores children's categories of emotion understanding from facial expressions onto two dimensional structure of emotion. Children of 89 from 3 to 5 years old were required to those facial expressions related the fourteen emotion terms. Facial expressions applied for experiment are used the photographs rated the degree of expression in each of the two dimensions (pleasure-displeasure dimension and arousal-sleep dimension) on a nine-point scale from 54 university students. The experimental results showed that children indicated the greater stability in arousal dimension than stability in pleasure-displeasure dimension. Emotions about sadness, sleepiness, anger and surprise onto two dimensions was understand very well, but emotions about fear, boredom were showed instability in pleasure-displeasure dimension. Specifically, 3 years old children indicated highly the perception in a degree of arousal-sleep than perception of pleasure-displeasure.

• Korean Journal of Cognitive Science
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• v.21 no.1
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• pp.127-143
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• 2010

This study explores children's sex differences of emotion discrimination from facial expressions based on two dimensional model of emotion. The study group consisted of 92 children, of 40, 52, and 64 months of age, and the rate of male and female children was male children (50%) and female children (50%). Children of 92 were required to choose facial expressions related the twelve emotion terms. Facial expressions applied for experiment are used the photographs rated the degree of expression in each of the two dimensions (pleasure-displeasure dimension and arousal-sleep dimension) on a nine-point scale from 54 university students. The experimental findings appeared that the sex differences were distinctly the arousal-sleep dimension than the pleasure-displeasure dimension. In the arousal-sleep dimensionoussleepness, anger, comfort, and loneliness' emotions showed large sex differences over 1 value. Especially, while male children showed high arousal more than female children in the emotions like 'sleepiness, anger and loneliness', female children showed high arousal more than male children in 'comfort' emotion.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 2006.06a
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• pp.246-250
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• 2006

얼굴의 중요한 특징부분을 잘 나타내는 깊이 에지 정보를 사용하면 표정과 조명변화로 인한 얼굴 픽셀의 밝기 값 변화에 대해 강인한 특징벡터를 생성할 수 있다. 본 논문에서는 깊이 에지(depth edge)를 이용한 새로운 특징벡터를 제안하고 그 유용성에 대하여 실험하였다. 새롭게 제안한 특징벡터는 얼굴의 깊이 에지 영상을 수평과 수직 방향으로 투영하여 얻어지는 에지 강도 히스토그램을 이용하기 때문에 얼굴의 움직임으로 인한 변형에 영향을 받지 않는다. 또한, 실시간 검출과 인식이 매우 용이하다. 제안한 깊이 에지 기반 특징벡터와 백색광 영상의 픽셀 값 기반 특징벡터에 대해 부공간 투영기반의 얼굴인식 알고리즘을 적용하여 성능을 비교 평가하였다. 실험 결과, 얼굴의 깊이 에지에 기반한 얼굴인식이 기존의 백색광만을 이용한 방법에 비해 높은 인식성능을 보였다