• Journal of KIISE:Software and Applications
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• v.31 no.6
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• pp.817-828
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• 2004

In this paper, we propose vector-based face generation system that uses montage and shading method and preserves designer(artist)'s style. Proposed system generates character's face similar to human face automatically using facial features that extracted from a photograph. In addition, unlike previous face generation system that uses contours, we propose the system is based on color and composes face from facial features and shade extracted from a photograph. Thus, it has advantages that can make more realistic face similar to human face. Since this system is vector-based, the generated character's face has no size limit and constraint. Therefore it is available to transform the shape freely and to apply various facial expressions to 2D face. Moreover, it has distinctiveness with another approaches in point that can keep artist's impression just as it is in result.

• Journal of Digital Convergence
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• v.20 no.2
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• pp.289-297
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• 2022

The purpose of this study was to investigate the perception of dental students based on their experiences of online classes after taking non-face-to-face education courses for all the school semesters in 2020. For the research method, an online survey was conducted on A survey was conducted on 161 dental students enrolled in A University. The analytical method was conducted through frequency analysis, correlation analysis, and multiple regression analysis. The survey analysis findings showed that the satisfaction of dental students' about the non-face-to-face education course was above 4.2, and the detailed items were in the order of the appropriateness of the attendance processing method, satisfaction with recorded video lectures, and the assessment method of the course grade. In the case of the factors that affect the satisfaction of non-face-to-face education courses, the learning system and assessment method were statistically significant. The online class type that is most preferred by the students is recorded video lectures, and the highest number of participants chose 21~30 minutes as the appropriate time for the class content. It is considered that the application of the online system will continue to be used together with face-to-face education courses in the education site and various university-level efforts like systematic support are required to achieve effective learning achievements. This study only investigated the non-face-to-face education operation conditions of A University, so it cannot be generalized to all universities, but it can be used as basic data to provide education curriculum design and supportive measures for the compatibility of face-to-face and non-face-to-face courses.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.1
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• pp.35-43
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• 2010

1D PCA utilized in the face appearance-based face recognition methods such as eigenface-based face recognition method may lead to less face representative power and more computational cost due to the resulting 1D face appearance data vector of high dimensionality. To resolve such problems of 1D PCA, 2D PCA-based face recognition methods had been developed. However, the face representation model obtained by direct application of 2D PCA to a face image set includes both face common features and face distinctive identity features. Face common features not only prevent face recognizability but also cause more computational cost. In this paper, we first develope a model of a face distinctive identity feature subspace separated from the effects of face common features in the face feature space obtained by application of 2D PCA analysis. Then, a novel robust face recognition based on the face distinctive identity feature subspace model is proposed. The proposed face recognition method based on the face distinctive identity feature subspace shows better performance than the conventional PCA-based methods (1D PCA-based one and 2D PCA-based one) with respect to recognition rate and processing time since it depends only on the face distinctive identity features. This is verified through various experiments using Yale A and IMM face database consisting of face images with various face poses under various illumination conditions.

• Journal of the Korean Society of Propulsion Engineers
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• v.23 no.4
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• pp.81-91
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• 2019

The 3-dimensional grain burn-back analysis is performed using the face offsetting method for calculating the solid rocket motor performance. The grain burning configuration analysis is a moving surface problem that calculates the regression of the burning surface. In the previous study, various moving interface analysis methods were applied for the grain burn-back analysis, but the results were imperfect. In this study, a 3-dimensional grain burn-back analysis module is developed using the face offsetting method, which combines the advantages of the existing moving interface analysis methods to increase the accuracy and robustness. As a result, the face offsetting method is proved to be efficient for the grain burn-back analysis.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.49-52
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• 2002

This paper presents a fast algorithm for face detection from color images on internet. We use Mahalanobis distance between standard skin color and actual pixel color on IQ color space to segment skin color regions. The skin color regions are the candidate face region. Further, the locations of eyes and mouth regions are found by computing average pixel values on horizontal and vertical pixel lines. The geometry of mouth and eye locations is compared to the standard face geometry to eliminate false face regions. Our Method is simple and fast so that it can be applied to face search engine for internet.

• Journal of Industrial Convergence
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• v.22 no.1
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• pp.169-176
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• 2024

The purpose of this study is a qualitative study to understand the meaning and essence of nursing students' non-face-to-face learning experience. It was conducted for two months from March to April 2022, targeting 12 students who participated in non-face-to-face learning, and three focus groups were formed and interviewed. Interview data were analyzed using Coaizzi's phenomenological research method. As a result of the study, 4 themes and 12 subtopics were derived. The four themes were 'freedom', 'efficiency', 'self-control', and 'lack of social skills'. Nursing students learned the meaning of non-face-to-face learning through non-face-to-face learning. Through the non-face-to-face learning experience of nursing students, the true meaning of non-face-to-face learning was analyzed and learned. The results of this study provided an understanding of the non-face-to-face learning experience of nursing students, which can be applied to the diversification of non-face-to-face education programs.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.108-113
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• 2009

Significant attention has recently been drawn to digital home photo albums that use face detection technology. The tendency can be found in home photo albums that people prefer to allocate concerned objects in the center of the image rather than the boundary when they take a picture. To improve detection performance and speed that are important factors of face detection task, this paper proposes a face detection method that takes spatial context information into consideration. Experiments were performed to verify the usefulness of the proposed method and results indicate that the proposed face detection method can efficiently reduce the false positive rate as well as the runtime of face detection.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.455-456
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• 2006

This paper presents an automatic pose-normalized 3D face data acquisition method using 2D and 3D information. We propose an automatic pose-normalized 3D face acquisition method that accomplishes 3D face modeling and 3D face pose-normalization at once. The proposed method uses 2D information with AAM (Active Appearance Model) and 3D information with 3D normal vector. The 3D face modeling system consists of 2 cameras and 1 projector. In order to verify proposed pose-normalized 3D modeling method, we made an experiment for 2.5D face recognition. The experimental result shows that proposed method is robust against pose variation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.11
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• pp.5605-5623
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• 2016

We propose a face recognition method that utilizes the LCP face descriptor. The proposed method applies a LoG mask to extract a face contour response, and employs the LCP algorithm to produce a binary pattern representation that ensures high recognition performance even under the changes in illumination, noise, and aging. The proposed LCP algorithm produces excellent noise reduction and efficiency in removing unnecessary information from the face by extracting a face contour response using the LoG mask, whose behavior is similar to the human eye. Majority of reported algorithms search for face contour response information. On the other hand, our proposed LCP algorithm produces results expressing major facial information by applying the threshold to the search area with only 8 bits. However, the LCP algorithm produces results that express major facial information with only 8-bits by applying a threshold value to the search area. Therefore, compared to previous approaches, the LCP algorithm maintains a consistent accuracy under varying circumstances, and produces a high face recognition rate with a relatively small feature vector. The test results indicate that the LCP algorithm produces a higher facial recognition rate than the rate of human visual's recognition capability, and outperforms the existing methods.

• Journal of Christian Education in Korea
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• v.69
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• pp.139-162
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• 2022

This study verified the effect of learning motivation on immersion by non-face-to-face class method. For this purpose, 101 college students majoring in early childhood education were selected as research subjects. The average age of the study subjects was 22.6 years old, and 51 students took non-real-time non-face-to-face classes, and 50 students took real-time non-face-to-face classes. The study measured the level of immersion and the type of learning motivation after the non-face-to-face class was finished. The measured data were analyzed using descriptive statistical analysis and multiple regression analysis. As a result, in the results for all students, the performance approach goal had the most influence on immersion, and the mastery goal orientation had the next effect. Performance avoidance orientation had no effect. For students in non-face-to-face classes, performance approach goal orientation had an effect on immersion, and for students in real-time non-face-to-face classes, mastery goal orientation had an effect. The implications that can be obtained from the results of this study are as follows. First, non-real-time non-face-to-face classes should cover basic knowledge and skills so that there are no mistakes and failures. Second, non-real-time non-face-to-face classes should allow tasks with appropriate difficulty to be performed with a deadline. Third, real-time non-face-to-face classes should lower the fear of mistakes and failures.