• The Research Journal of the Costume Culture
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• v.15 no.3 s.68
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• pp.431-445
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• 2007

The purpose of this study was to analyze and theorize the characteristics of femme fatale in fashion illustration since 1980. The method of this study was to analyze the documentaries for theoretical studies about femme fatale and the visual characteristics in fashion illustration works since 1980. The results of this study were as follows: Femme fatale expressed in the general realm of art was icon of fatal and seductive eroticism in late 19th century. She is composed of diverse images like mythology, exoticism, fear and sensuality. The characteristics of her image in fashion illustration were expressed into de-body image by union of animal and female body, or machine and female body, duplicity of death and sexuality, sexual decadence or abnormality and powerful masculine taste. First, de-body image by union of animal and female body, or machine and female body was expressed in transformed mythical image or bizarre and demonic image, grotesque image linked by picture of female body and painting of animal image, and cyborg image linked by machine and realistic female body by digital media. Second, duplicity of death and sexuality was expressed in juxtaposition by sexual pose, body and something metaphorical and symbolic depiction and de-constructive depiction of death. Third, sexual decadence or abnormality was expressed in fetishistic style, obscene depiction of cheap and hedonistic sexuality, masochistic depiction like antisocial and diseased sex appeal. Forth, powerful masculine taste was expressed in man's face, body, pose, masculine fashion, man's role related to crime and threatening weapon, etc. As mentioned above, femme fatale in fashion illustration was expressed in diverse images by fashion illustrator's point of view. Although she was originated by men's fantastic vision, she brings a catharsis to human being. And she is also recognized as new paradigm and positive cultural sign in our times.

• Korean Journal of Computational Design and Engineering
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• v.22 no.1
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• pp.89-99
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• 2017

In order to make a virtual endoscopy system effective for exploring the interior of the 3D model of a human organ, it is necessary to generate an accurate navigation path located inside the 3D model and to obtain consistent camera position and pose estimation along the path. In this paper, we propose an approach to virtual navigation of blood vessels, which makes proper use of orthogonal contours and skeleton curves. The approach generates the orthogonal contours and the skeleton curves from the 3D mesh model and its voxel model, all of which represent the blood vessels. For a navigation zone specified by two nodes on the skeleton curves, it computes the shortest path between the two nodes, estimates the positions and poses of a virtual camera at the nodes in the navigation zone, and interpolates the positions and poses to make the camera move smoothly along the path. In addition to keyboard and mouse input, intuitive hand gestures determined by the Leap Motion SDK are used as user interface for virtual navigation of the blood vessels. The proposed approach provides easy and accurate means for the user to examine the interior of 3D blood vessels without any collisions between the camera and their surface. With a simple user study, we present illustrative examples of applying the approach to 3D mesh models of various blood vessels in order to show its quality and usefulness.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.686-689
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• 2018

3D 손 포즈 추정(Hand Pose Estimation, HPE)은 스마트 인간 컴퓨터 인터페이스를 위해서 중요한 기술이다. 이 연구에서는 딥러닝 방법을 기반으로 하여 단일 RGB-Depth 카메라로 촬영한 양손의 3D 손 자세를 실시간으로 인식하는 손 포즈 추정 시스템을 제시한다. 손 포즈 추정 시스템은 4단계로 구성된다. 첫째, Skin Detection 및 Depth cutting 알고리즘을 사용하여 양손을 RGB와 깊이 영상에서 감지하고 추출한다. 둘째, Convolutional Neural Network(CNN) Classifier는 오른손과 왼손을 구별하는데 사용된다. CNN Classifier 는 3개의 convolution layer와 2개의 Fully-Connected Layer로 구성되어 있으며, 추출된 깊이 영상을 입력으로 사용한다. 셋째, 학습된 CNN regressor는 추출된 왼쪽 및 오른쪽 손의 깊이 영상에서 손 관절을 추정하기 위해 다수의 Convolutional Layers, Pooling Layers, Fully Connected Layers로 구성된다. CNN classifier와 regressor는 22,000개 깊이 영상 데이터셋으로 학습된다. 마지막으로, 각 손의 3D 손 자세는 추정된 손 관절 정보로부터 재구성된다. 테스트 결과, CNN classifier는 오른쪽 손과 왼쪽 손을 96.9%의 정확도로 구별할 수 있으며, CNN regressor는 형균 8.48mm의 오차 범위로 3D 손 관절 정보를 추정할 수 있다. 본 연구에서 제안하는 손 포즈 추정 시스템은 가상 현실(virtual reality, VR), 증강 현실(Augmented Reality, AR) 및 융합 현실 (Mixed Reality, MR) 응용 프로그램을 포함한 다양한 응용 분야에서 사용할 수 있다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3924-3940
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• 2020

Dynamic hand gesture recognition(d-HGR) plays an important role in human-computer interaction(HCI) system. With the growth of hand-pose estimation as well as 3D depth sensors, depth, and the hand-skeleton dataset is proposed to bring much research in depth and 3D hand skeleton approaches. However, it is still a challenging problem due to the low resolution, higher complexity, and self-occlusion. In this paper, we propose a hand-shape feature extraction(HSFE) network to produce robust hand-shapes. We build a hand-shape model, and hand-skeleton based on LSTM to exploit the temporal information from hand-shape and motion changes. Fusion between two models brings the best accuracy in dynamic hand gesture (DHG) dataset.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.6
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• pp.3437-3442
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• 2013

The high incidence of gastric cancer and consequent mortality pose severe threats to human health. Early screening, diagnosis and treatment are the key to improve the prognosis of the patients with gastric cancer. Gastroscopy with biopsy is an efficient method for the diagnosis of early gastric cancer, but the associated discomfort and high cost make it difficult to be a routine method for screening gastric cancer. Serum tumor marker assay is a simple and practical method for detection of gastric cancer, but it is limited by poor sensitivity and specificity. Therefore, people have been looking for novel serum markers of gastric cancer in recent years. Here we review the novel serum tumor markers of gastric cancer and their diagnostic significance, focusing on the discoveries from serum proteomics analyses and epigenetics researches.

• Journal of the Korean Home Economics Association
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• v.40 no.2
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• pp.67-86
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• 2002

The purpose of this research is to offer a method to derive the body shapes and pose factors with resets from analyzing factors by using the measurement values of human body. 297 male subjects in their twenties participated in this study. 54 anthropometric and 35 photographic measurements were taken from each subject. Data is the several typical items selected among items and you have to make an index value by using these typical items and convert it. The index has high correlation with each item, is easy to be measured and is to be used after selecting an important item in designing prototype. With results of analyzing reliability level by each item, correlation and items that factor loading is low, the item that the correlation is high is to be removed within the range that maintains the reliability level. Five factors of the front part and seven factors of the profile came to be derived from this kind of process.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.12 no.1
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• pp.8-15
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• 2003

The cylindrical object such as a water pipe or an oil pipeline are widely used in the infrastructure. Those pipes should be inspected periodically by human or a robot. However, since there is no edge or vertex in the pipe, it is very difficult for the robot to navigate along the pipe. In this paper in order to guide the robot along the axis of the pipe, an algorithm which find the axis using the measured range data from the robot to the pipe wall is developed The algorithm is verified using both the simulated range data and the measured one.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.299-302
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• 2001

The statistical analysis of the feature extraction and the neural networks are proposed to recognize a human face. In the preprocessing step, the normalized skin color map with Gaussian functions is employed to extract the region of face candidate. The feature information in the region of the face candidate is used to detect the face region. In the recognition step, as a tested, the 120 images of 10 persons are trained by the backpropagation algorithm. The images of each person are obtained from the various direction, pose, and facial expression. Input variables of the neural networks are the geometrical feature information and the feature information that comes from the eigenface spaces. The simulation results of$.$10 persons show that the proposed method yields high recognition rates.

• Asian-Australasian Journal of Animal Sciences
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• v.23 no.9
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• pp.1250-1260
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• 2010

Mycotoxins are secondary metabolites produced by fungi. These toxins pose serious health concerns to animals as well as human beings. Biodegradation of these mycotoxins has been considered as one of the best strategies to decontaminate food and feedstuffs. Biodegradation employs the application of microbes or enzymes to contaminated food and feedstuffs. Ruminants are considered to be resistant to the adverse effects of mycotoxins presumably due to the biodegrading ability of rumen microbes compared to mono-gastric animals. Therefore, rumen microbial source or microbial enzyme could be a great asset in biological detoxification of mycotoxins. Isolation and characterization of pure culture of rumen microorganisms or isolation and cloning of genes encoding mycotoxin-degrading potential would prove to have overall beneficial impact in the food and feed industry.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.270-272
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• 2009

본 연구에서는 자동차 사고나 뇌졸중 등에 의해 경추 이하의 마비나 손, 발 등의 움직임은 자유롭지 않은 사람들의 컴퓨터 사용을 돕고자 손이나 발을 이용하지 않고 머리의 움직임과 눈의 깜박임만으로 컴퓨터 마우스 제어가 가능한 장치를 제안하였다. 마우스의 좌우, 상하 이동은 각속도 센서를 이용하여 머리의 움직임으로 유발하고, 클릭과 더블 클릭은 광 센서를 시야를 방해하지 않는 위치에 장착하여 감지할 수 있도록 하였다. 제안한 마우스를 Quick Glance를 이용한 것과 비교해 보고 문자를 입력함에 있어 dasher을 이용하는 것과 윈도우에서 제공하는 화상키보드를 이용하는 것을 비교해 보았다. 공간 이동 능력과 이벤트 검출을 비교한 실험에서는 좌우, 상하 이동은 기존 마우스와 비교하여 속도 면에서는 큰 차이는 없었으나, 정확도가 조금 떨어지는 이유로 인하여 소요시간이 $3{\sim}4$배 정도 더 필요하였다. 그러나 Quick glance와 비교결과에서는 약 14%정도 빠랐고 dasher을 이용하여 문자를 입력함에 있어서도 약 32% 이상 빠르게 문자를 입력할 수 있었다. 실험 결과 눈이 쉽게 피로해지는 Quick glance를 이용하는 것보다 제안한 마우스를 사용하는 것이 더 효과적이었다.