• The Journal of Korean Academy of Prosthodontics
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• v.33 no.1
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• pp.164-175
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• 1995

This study was designed to investigate the effect of Gibson's smile exercise. The author took the smile photographs of 35 university students who appeared unnatural smiles though they had good dentition or well restored state of their teeth. The author explained Gibson's smile exercise and they trained their perioral muscles during 4 weeks at home. The smile photographs were taken at regular intervals, before the smile exercise, 2 weeks after and 4 weeks after the smile exercise. And then, esthetic smile scores were estimated by 10 appraisers who were dentists. Some questionares were taken aftersmile exercise. And acquired scores were analized statistically using the SPSS program. The results obtained were as follows. 1. The smile scores of 2 weeks after and 4 weeks after the smile exercise were higher than before the smile exercise. 2. The smile scores of 4 weeks after the smile exercise were higher than 2 weeks after the smile exercise. 3. The smile scores of the group interested in smiles were higher than the group not interested in smiles at 2 weeks after and 4 weeks after the smile exercise, but before the smile exercise there was no difference between two groups.

• The korean journal of orthodontics
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• v.47 no.1
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• pp.31-38
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• 2017

Objective: This study aimed to quantitatively assess the relationship of smile esthetic variables with various types of malocclusion, and identify the cephalometric factors affecting smile measurements. Methods: This retrospective study included 106 patients who were treated with retention at the orthodontic department of Taipei Medical University Hospital. Hard-tissue variables were measured using lateral cephalographic tracings, and nine smile esthetic variables were measured using facial photographs. The patients were divided into three groups according to their overjet (< 0, 0-4, and > 4 mm). An analysis of variance was conducted to compare the pretreatment cephalometric variables and smile esthetic variables among the three groups. Multiple linear regression analysis was performed to identify the cephalometric factors affecting the smile measurements in each group. Results: Except the upper midline and buccal corridor ratio, all of the smile measurements differed significantly among the three groups before orthodontic treatment. Some of the smile characteristics were correlated with the cephalometric measurements in different types of malocclusion. The overjet was the major factor influencing the smile pattern in all three types of malocclusion. Conclusions: Smile characteristics differ between different types of malocclusion; the smile may be influenced by skeletal pattern, dental procumbency, or facial type. These findings indicate that establishment of an optimal horizontal anterior teeth relationship is the key to improving the smile characteristics in different types of malocclusion.

• The Journal of Korean Academy of Prosthodontics
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• v.34 no.4
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• pp.687-697
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• 1996

There has been a lot of research into the essence of the smile, but so far just a few studies have been done on the relationship between personality and smile. On the assumption that smile aesthetics are closely related to individual physical condition and psychological state, this study investigated the correlation between personality factors and smile scores. The Personality Factor Questionnaire test was administered to 60 university students (male : 30, female : 30) who have no teeth missing, no experience of orthodontic or prosthodontic treatment and good dentition. Then, portraits were taken in a full smile. Esthetic smile scores were estimated by 10 appraisers who were dentists. These scores were analyzed statistically using the SAS program. The following results were obtained. 1. Personality factors of Warmth, Stableness, Surgency, Boldness, Untroubled-adequacy, Group-dependence, Relaxation, Extraversion, Low anxiety were positively correlated to the aesthetic level of smile. 2. For females, personality factors had greater influence on smile aesthetics, whereas male smile aesthetics were less influenced by personality factors.

• Journal of IKEEE
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• v.27 no.4
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• pp.464-471
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• 2023

In this paper, we propose a method to reduce age distortion in facial expression image generation using StyleGAN Encoder. The facial expression image generation process first creates a face image using StyleGAN Encoder, and changes the expression by applying the learned boundary to the latent vector using SVM. However, when learning the boundary of a smiling expression, age distortion occurs due to changes in facial expression. The smile boundary created in SVM learning for smiling expressions includes wrinkles caused by changes in facial expressions as learning elements, and it is determined that age characteristics were also learned. To solve this problem, the proposed method calculates the correlation coefficient between the smile boundary and the age boundary and uses this to introduce a method of adjusting the age boundary at the smile boundary in proportion to the correlation coefficient. To confirm the effectiveness of the proposed method, the results of an experiment using the FFHQ dataset, a publicly available standard face dataset, and measuring the FID score are as follows. In the smile image, compared to the existing method, the FID score of the smile image generated by the ground truth and the proposed method was improved by about 0.46. In addition, compared to the existing method in the smile image, the FID score of the image generated by StyleGAN Encoder and the smile image generated by the proposed method improved by about 1.031. In non-smile images, compared to the existing method, the FID score of the non-smile image generated by the ground truth and the method proposed in this paper was improved by about 2.25. In addition, compared to the existing method in non-smile images, it was confirmed that the FID score of the image generated by StyleGAN Encoder and the non-smile image generated by the proposed method improved by about 1.908. Meanwhile, as a result of estimating the age of each generated facial expression image and measuring the estimated age and MSE of the image generated with StyleGAN Encoder, compared to the existing method, the proposed method has an average age of about 1.5 in smile images and about 1.63 in non-smile images. Performance was improved, proving the effectiveness of the proposed method.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2007.04a
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• pp.30-33
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• 2007

DSMC method is now widely accepted CFD approach to compute and simulate the nozzle plume in rarefied regimes. In this study, using SMILE(Statistical Modeling in Low-density Environment) code which was developed in ITAM, Russia and coded using DSMC method, the internal flow of the Rothe micronozzle was simulated. Moreover, to show the validity of the SMILE code, the centerline temperatures according to the Reynold's number were compared with the ones obtained by the Rothe's experiment.

• The korean journal of orthodontics
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• v.26 no.2 s.55
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• pp.197-204
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• 1996

This study was performed to mark the criteria of the eathetic smile that was necessary to improve the esthetic problem in oral maxillo-facial region. The facial straight photographs of 62 adults(30 males, 32 females : 19-24 years old) in resting position and during smile were taken. The measurements and proportion of lip-teeth relationship during smile were statistically analyzed with photogrammetry. The following results wow obtained : 1. In the evaluation of the change of lips, smile line ratio was 0.93, buccal corridor ratio was 0.63, and smile symmetry ratio was 0.96. 2. The width of mouth during smile was 1.31 times of the width inthe resting position and 0.48 times of face width. 3. The upper lip height during smile was 0.69 times of the height in the resting position and the lower lip height during smile was 0.93 times of the height in the resting position. 4. The mean exposed lenght of upper central incisor was 9.96mm. Maxillary incisor exposure was significantly correlated with the upper lip change ratio, mouth width change ratio, and buccal corridor ratio.

• Journal of Korea Multimedia Society
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• v.14 no.11
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• pp.1373-1382
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• 2011

In this study, we propose an automated smile analysis system for self smile training. The proposed system detects the face area from the input image with the AdaBoost algorithm, followed by identifying facial features based on the face shape model generated by using an ASM(active shpae model). Once facial features are identified, the lip line and teeth area necessary for smile analysis are detected. It is necessary to judge the relationship between the lip line and teeth for smiling degree analysis, and to this end, the second differentiation of the teeth image is carried out, and then individual the teeth areas are identified by means of histogram projection on the vertical axis and horizontal axis. An analysis of the lip line and individual the teeth areas allows for an automated analysis of smiling degree of users, enabling users to check their smiling degree on a real time basis. The developed system in this study exhibited an error of 8.6% or below, compared to previous smile analysis results released by dental clinics for smile training, and it is expected to be used directly by users for smile training.

• The Journal of Korean Academy of Prosthodontics
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• v.31 no.4
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• pp.542-548
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• 1993

This study was designed to investigate the effect of missing teeth, prosthesis and malalignment on the smile. The full smile photographs of 145 Korean adults(male 114 : female 31) were taken and classified by the lip pattern, the relationship between the lip and the teeth, and the number of teeth displayed in a smile. Besides, the esthetic smile score were estimated by five dentists. Obtained data were compared and analyzed. The results obtained were as follows : 1. The esthetic level of missing teeth group and malaligned group was lower than that of the normal group. 2. The esthetic level of prosthesis group had no difference with that of the normal group. 3. The Number of teeth displayed in a smile had the most effect on the esthetic level in each experimental group.

• 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.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.29A no.4
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• pp.64-73
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• 1992

This paper presents the design of multi-level logic optimization algorithm and the development of the SMILE system based on the algorithm. Considering the fanin constraints in algorithmic level, SMILE performs global and local optimization in a predefined sequence using heuristic information. Designed under the Sogang Silicon Compiler design environment, SMILE takes the SLIF netlist or Berkeley equation formats obtained from high-level synthesis process, and generates the optimized circuits in the same format. Experimental results show that SMILE produces the promising results for some circuits from MCNC benchmarks, comparable to the popularly used multi-level logic optimization system, MIS.