• Journal of the Korea Society of Computer and Information
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• v.25 no.5
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• pp.1-9
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• 2020

In this paper, we propose a model that performs more natural facial attribute editing by utilizing mask information in the hair and hat region. STGAN, one of state-of-the-art research of facial attribute editing, has shown results of naturally editing multiple facial attributes. However, editing hair-related attributes can produce unnatural results. The key idea of the proposed method is to additionally utilize information on the face regions that was lacking in the existing model. To do this, we apply three ideas. First, hair information is supplemented by adding hair ratio attributes through masks. Second, unnecessary changes in the image are suppressed by adding cycle consistency loss. Third, a hat segmentation network is added to prevent hat region distortion. Through qualitative evaluation, the effectiveness of the proposed method is evaluated and analyzed. The method proposed in the experimental results generated hair and face regions more naturally and successfully prevented the distortion of the hat region.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.10
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• pp.43-50
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• 1997

In this paper, we present a method that can recognize face images by use of a sparse population code that is a learning model about a receptive fields of the simple cells in the primary visual cortex. Twenty front-view facial images form twenty persons were used for the training process, and 200 varied facial images, 20 per person, were used for test. The correct recognition rate was 100% for only the front-view test facial images, which include the images either with spectacles or of various expressions, while it was 90% in average for the total input images that include rotated faces. We analyzed the effect of nonlinear functon that determine the sparseness, and compared recognition rate using the sparese population code with that using eigenvectors (eigenfaces), which is compact code that makes contrast with the sparse population code.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.351-354
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• 2011

This paper discusses on facial features extraction based on proposed skin color model. Different parts of face from input image are segmented based on skin color model. Moreover, this paper also discusses on concept to detect the eye and mouth position on face. A height and width ratio (${\delta}=1.1618$) based technique is also proposed to accurate detection of face region from the segmented image. Finally, we have cropped the desired part of the face. This exactly exacted face part is useful for face recognition and detection, facial feature analysis and expression analysis. Experimental results of propose method shows that the proposed method is robust and accurate.

• Proceedings of the Korea Contents Association Conference
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• 2006.11a
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• pp.340-343
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• 2006

With an assumption that the view point of a given society and time on facial attractiveness can be inferred by analyzing winners of beauty pageant faces, the trends in the physical measures of miss Koreas were investigated. A classification model of affective facial impressions was used to obtain the physical measures of the faces and classifying them into a face-type category. The number of face images analyzed in the study were 171 winners of Miss Korea Contest. The results show that there has been a shift in the impression from 'mature' to 'babyish' for the Korean beauty-contest winners for the last 50 years.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.6
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• pp.513-519
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• 2013

The current vision-based approaches for emotion recognition, such as facial expression analysis, have many technical limitations in real circumstances, and are not suitable for applications that use them solely in practical environments. In this paper, we propose an approach for emotion recognition by combining extrinsic representations and intrinsic activities among the natural responses of humans which are given specific imuli for inducing emotional states. The intrinsic activities can be used to compensate the uncertainty of extrinsic representations of emotional states. This combination is done by using PRMs (Probabilistic Relational Models) which are extent version of bayesian networks and are learned by greedy-search algorithms and expectation-maximization algorithms. Previous research of facial expression-related extrinsic emotion features and physiological signal-based intrinsic emotion features are combined into the attributes of the PRMs in the emotion recognition domain. The maximum likelihood estimation with the given dependency structure and estimated parameter set is used to classify the label of the target emotional states.

• Imaging Science in Dentistry
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• v.31 no.4
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• pp.199-204
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• 2001

Purpose : To assess the relationship between soft tissue asymmetry and bone tissue asymmetry using the standardized photographs and the posteroanterior (PA) cephalometric radiographs in mandibular asymmetric patients. And to clarify that the lack of morphologic balance among different skeletal components can often be masked by compensatory soft tissue contributions. Methods: Experimental group consisted of 58 patients whose chief complaints were facial asymmetry, they were taken with standardized facial photographs and PA cephalometric radiographs. Control group consisted of 30 persons in the normal occlusion. The reproducibility of the facial photograph was confirmed by model test. The differences of fractional vertical heightand horizontal width from standardized facial photographs and PA cephalometric radiographs were compared and analyzed. Results: The difference of fractional vertical bone height was 0.63 and fractional vertical soft height was 0.58 in control group, 3.10 and 2.01 in asymmetric group, respectively. The difference of fractional horizontal bone width was 0.52 and fractional horizontal soft width was 0.70 in control group, 2.51 and 1.70 in asymmetric group, respectively. Both soft and bone tissue showed significant difference between control and asymmetric group (p<0.05). The difference of bone tissue was greater than that of soft tissue (p<0.05) in the experimental group but, not in control group. Conclusions: Soft tissue components may compensate for underlying skeletal imbalances.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.38
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• pp.37.1-37.5
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• 2016

Background: The dimensions and shape of the forehead determine the esthetics of the upper third of the face. Korean young people consider a broad and smooth, rounded forehead more attractive. As a result, frontal augmentation becomes more popular in patients with dentofacial deformities. Various surgical procedures and materials have been used in frontal augmentation surgery, with associated advantages and disadvantages. Silicone is a good candidate for frontal augmentation. The author presents two cases of esthetic frontal augmentation with a prefabricated silicone implant in female patients with dentofacial deformities. Case presentation: In case 1, a 24-year-old female patient underwent frontal augmentation surgery with simultaneous maxillomandibular and zygomatic osteotomies to correct facial asymmetry. A silicone implant was fabricated preoperatively using a positive template stone mold of her forehead. In case 2, a 23-year-old female patient underwent total facial contouring surgery including frontal augmentation for improved facial esthetics. A computed tomography (CT)-guided rapid prototype (RP) model was used to make the silicone implants. The operative procedure was safe and simple, and the silicone implants were reliable for a larger degree of frontal augmentation. Six months later, both patients had recovered from the surgery and were satisfied with their frontal shape and projection. Conclusions: Frontal augmentation with silicone implants can be an effective adjuvant strategy to improve facial esthetics in patients with a flat and narrow forehead who undergo orthognathic reconstruction or total facial contouring surgery.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.4
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• pp.705-711
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• 2003

An automatic face and facial feature points(FFPs) detection system is proposed. A face is represented as a graph where the nodes are placed at facial feature points(FFPs) labeled by their Gabor features and the edges are describes their spatial relations. An innovative flexible feature matching is proposed to perform features correspondence between models and the input image. This matching model works likes random diffusion process in !be image space by employing the locally competitive and globally corporative mechanism. The system works nicely on the face images under complicated background, pose variations and distorted by facial accessories. We demonstrate the benefits of our approach by its implementation on the face identification system.

• Journal of International Society for Simulation Surgery
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• v.2 no.2
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• pp.80-82
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• 2015

The mandibuloplasty for the facial aesthetic reason has been the one of the most popular procedures in aesthetic facial bone surgery in East Asia. Most East Asian women prefer smaller-looking and smooth-shaped facial contour. Prominent mandible angle which are common in Asia would be the main problem for smooth facial contour. In addition, recently, the mandibular body and broad chin shape also are known to be remodeled in order to get the ideal smooth facial shape. However, mandibuloplasty is not that easy to cut because many patients has inward mandibular angle and the visual field in operation is limited. The aim of this trial is to try to provide the prefabricated cutting guide for the symmetric and appropriate mandibuloplasty with the surgeons. Preoperative computed tomography(CT) data were processed for the patient and computer simulation model was produced. Then, mandibuloplasty was done on the computer simulation screen. Based on this data, customized cutting guide was made. This prefabricated cutting guide was used in real mandibuloplasty bilaterally. Premade cutting guide for the mandibuloplasty based on the computer simulation turned out to be very successful in this patient. Individualized approach for each patient could be an ideal way to manage the patients in near future.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.2
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• pp.165-171
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• 2017

It is difficult to recognize Human's facial expression in the real-world. For these reason, when database and test data have similar condition, we can accomplish high accuracy. Solving these problem, we need to many facial expression data. In this paper, we propose the algorithm for gathering many facial expression data within various environment and gaining high accuracy quickly. This algorithm is training initial model with the ASSL (Active Semi-Supervised Learning) using deep learning network, thereafter gathering unlabeled facial expression data and repeating this process. Through using the ASSL, we gain proper data and high accuracy with less labor force.