• Cartoon and Animation Studies
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• s.41
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• pp.57-73
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• 2015

A pose is an important component in the animation with timing and spacing. Pose is the key to describe the story-telling or how the animation behavior. Key animation method is Straight Ahead and pose to pose method. Many animaters have been using these two methods, or by a mix of two ways. It is possible that computer animation make a pose using interpolation between keyframes. The many animators of computer animation are using pose to pose in their work. It is depend on good and strong pose that make audience understand a story or a situation. This makes animators to be efficient of inefficient operation. In this study, according to the effective good pose to catch proposes four ways. There are four methods of making pose that are stretch and squash, the height of the character, the center of weight, step. The law of 12 kinds of Disney Animation is a good reference for the study.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.63-69
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• 2004

This paper proposes a novel method for achieving pose-invariant face recognition using cylindrical model. On the assumption that a face is shaped like that of a cylinder, we estimate the object's pose and then extract the frontal face image via a pose transform with previously estimated pose angle. By employing the proposed pose transform technique we can increase the face recognition performance using the frontal face images. Through representative experiments, we achieved an increased recognition rate from 61.43% to 94.76% by the pose transform. Additionally, the recognition rate with the proposed method achieves as good as that of the more complicated 3D face model.

• Journal of Integrative Natural Science
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• v.2 no.2
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• pp.55-58
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• 2009

A ligand-receptor docking program is an indispensible tool in modern pharmaceutical design. An accurate prediction of small molecular docking pose to a receptor is essential in drug design as well as molecular recognition. An effective docking program requires the ability to locate a correct binding pose in a surprisingly complex conformational space. However, there is an inherent difficulty to predict correct binding pose. The odds are more demanding than finding a needle in a haystack. This mainly comes from the flexibility of both ligand and receptor. Because the searching space to consider is so vast, receptor rigidity has been often applied in docking programs. Even nowadays the receptor may not be considered to be fully flexible although there have been some progress in search algorithm. Improving the efficiency of searching algorithm is still in great demand to explore other applications areas with inherently flexible ligand and/or receptor. In addition to classical search algorithms such as molecular dynamics, Monte Carlo, genetic algorithm and simulated annealing, rather recent algorithms such as tabu search, stochastic tunneling, particle swarm optimizations were also found to be effective. A good search algorithm would require a good balance between exploration and exploitation. It would be a good strategy to combine algorithms already developed. This composite algorithms can be more effective than an individual search algorithms.

• Journal of KIISE:Software and Applications
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• v.31 no.7
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• pp.929-938
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• 2004

This paper proposes a pose-invariant face recognition method using cylindrical model and stereo camera. We divided this paper into two parts. One is single input image case, the other is stereo input image case. In single input image case, we normalized a face's yaw pose using cylindrical model, and in stereo input image case, we normalized a face's pitch pose using cylindrical model with previously estimated pitch pose angle by the stereo geometry. Also, since we have an advantage that we can utilize two images acquired at the same time, we can increase overall recognition performance by decision-level fusion. Through representative experiments, we achieved an increased recognition rate from 61.43% to 94.76% by the yaw pose transform, and the recognition rate with the proposed method achieves as good as that of the more complicated 3D face model. Also, by using stereo camera system we achieved an increased recognition rate 5.24% more for the case of upper face pose, and 3.34% more by decision-level fusion.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.1
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• pp.111-118
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• 2022

In computer vision research, the two-dimensional human pose is a very extensive research direction, especially in pose tracking and behavior recognition, which has very important research significance. The acquisition of human pose targets, which is essentially the study of how to accurately identify human targets from pictures, is of great research significance and has been a hot research topic of great interest in recent years. Human pose recognition is used in artificial intelligence on the one hand and in daily life on the other. The excellent effect of pose recognition is mainly determined by the success rate and the accuracy of the recognition process, so it reflects the importance of human pose recognition in terms of recognition rate. In this human body gesture recognition, the human body is divided into 17 key points for labeling. Not only that but also the key points are segmented to ensure the accuracy of the labeling information. In the recognition design, use the comprehensive data set MS COCO for deep learning to design a neural network model to train a large number of samples, from simple step-by-step to efficient training, so that a good accuracy rate can be obtained.

• Korean Journal of Human Ecology
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• v.7 no.3
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• pp.15-33
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• 2004

A precise understanding of the human form in static pose serves as the basis of designing clothing. When the human body is in motion, however, even an article of clothing designed to fit the human form in static pose can pull and change, thus restricting the body. In order to increase the fit of the clothing, which may be termed the second skin, its form and measurements therefore must be determined in correlation not only with the formal characteristics of the human body, in static pose but also with its functional characteristics in motion, as caused by the movements of the human body. In this study, the motion factor was selected as the primary basis for designing slacks with good fit in both static and moving states. By indentifying the areas in which lower limb movement cause significant changes in body surface lines, we suggest several application methods for designing slacks. Using unmarried female university students aged 18 - 24 as subjects, a total of 32 body surface categories (15 body surface lines and 17 body surface segment lines) were measured in one static and 9 movement poses. In particular, expansion and contraction levels and rates were measured and used in the analysis. The analysis first involved the calculation of the average measurement per body part in body surface line in static pose as well as of the average expansion and contraction levels and rates in 9 lower limb movements. Two-way MANOVA and multiple comparison analysis (Tukey) were conducted on movements and individual somatotypes regarding measurement per body part and expansion and contraction rates. Body parts whose measurements of body surface lines differed significantly in body surface line in static pose versus in movement were then identified. The results of this study are as follows. First, changes in body surface lines caused by lower limb movements were significant in all body surface lines of the lower trunk, both horizontal and vertical, with the exception of abdomen girth, midway thigh girth, ankle girth, hip length, and posterior knee girth. Second, significantly expanded 10 body surface lines in moving pose were detected and illustrated in table 4. These body parts should be studied in designing or pattern designing, especially for close-fitting pants, in using stretch fabric, and in sensory evaluation of good fit during movement.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.5
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• pp.134-142
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• 1997

In this study, we proposed the wire parallel mechanism that can be used to measure a full pose of a robot. It is composed of six parallel links using wire. The position and orientation of the end effectorf of a robot are calculated using the length of wires which is measured by the encoder. The complex non- linear equations of the forward kinematics are solved by using a numerical method, and the unique solution is obtained from the geometric configuration of the device. The length error of the wire which occurs in static condition is compensated by the relational equation that considered longitudinal extension and defoection of the wire. Through this work, we known that the proposed device has a good accuracy( .+-. 0.01mm) in a large measuring region, so it can be used effectively in a callibration of a robot which required a low cost.

• Journal of Digital Convergence
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• v.15 no.12
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• pp.489-494
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• 2017

In spite of lots of differences in the production process of film animation, the animating method through computer is not much different between game animation and film animation. It is because the principles of film animation are also emphasized for the production of game animation. This study aims to consider the line of action showing the direction of movement and flow of energy among many considerations for the character pose work in case when producing game animation. Starting from the basic theory of drawing, the line of action plays a role of bible in the pose work including cell animation and 3D animation. After examining the theoretical background through preceding researches in order to understand the application of the line of action to the pose work of game characters, the poses of hero characters of a 3D online game 'Over Watch' were collected and then lines were directly drawn to analyze them. And as a result, the pose of characters with simple and clear 'Line of action' was good. This study aimed to consider the expression techniques of character pose in the production of game animation, which is expected to be used as an important reference for game animators at work.

• Journal of Korea Multimedia Society
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• v.24 no.5
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• pp.659-666
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• 2021

With the continuous development of deep learning, human behavior recognition algorithms have achieved good results. However, in a multi-person recognition environment, the complex behavior environment poses a great challenge to the efficiency of recognition. To this end, this paper proposes a multi-person pose estimation model. First of all, the human detectors in the top-down framework mostly use the two-stage target detection model, which runs slow down. The single-stage YOLOv3 target detection model is used to effectively improve the running speed and the generalization of the model. Depth separable convolution, which further improves the speed of target detection and improves the model's ability to extract target proposed regions; Secondly, based on the feature pyramid network combined with context semantic information in the pose estimation model, the OHEM algorithm is used to solve difficult key point detection problems, and the accuracy of multi-person pose estimation is improved; Finally, the Euclidean distance is used to calculate the spatial distance between key points, to determine the similarity of postures in the frame, and to eliminate redundant postures.

• The Journal of Korea Robotics Society
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• v.6 no.4
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• pp.344-352
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• 2011

A mobile manipulator is a system with a robotic manipulator mounted on top of a mobile base. It has both indoor and outdoor applications for transporting or transferring materials. When a user gives commands, they are usually at high levels such as "move the object to the table," or "tidy the room." By intelligently decomposing these complex commands into several subtasks, the mobile manipulator can perform the tasks with a greater efficiency. One of the crucial subtasks for these commands is the pick-and-place task. For the mobile manipulator, selection of a good base position and orientation is essential to accomplishing this task. This paper presents an algorithm that determines one of the position and orientation of a mobile manipulator in order to complete the pick-and-place task without human intervention. Its effectiveness are shown for a mobile manipulator with 9 degrees-of-freedom in simulation.