• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.3
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• pp.157-165
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• 2014

To develop a compact vehicle for women, the most important areas are 'behavioral characteristics, life style and driving posture'. Static AM95%ile manikin is used for package guideline. Since women's characteristics and sitting position are different from men, however, the guideline cannot satisfy women drivers. Therefore, the goal of this study is to make the database with dynamic women's driving posture and behavioral characteristics at compact vehicle. Research process will be made as follows. Firstly, through the online/offline survey and statistic analysis, lifestyle and behavioral characteristics (discomfort elements) of women are extracted. Secondly, the author performs scenario test to acquire the discomfort value of driving situation and life style. 3D models of women's manikin and driving posture were created by CATIA HUMAN. The 3D models are used for the purpose of analyzing women's driving posture. Finally, with the ANOVA result and comparison between real driving posture and package guidelines, the author is able to suggest the main issue for women drivers.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.4
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• pp.367-375
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• 2002

Inverse kinematics is a very useful method for control]ing the posture of an articulated body. In most inverse kinematics processes, the major matter of concern is not the posture of an articulated body itself but the position and direction of the end effector. In some applications such as 3D character animations, however, it is more important to generate an overall natural posture for the character rather than place the end effector in the exact position. Indeed, when an animator wants to modify the posture of a human-like 3D character with many physical constraints, he has to undergo considerable trial-and-error to generate a realistic posture for the character. In this paper, the Inductive Inverse Kinematics(IIK) algorithm using a Uniform Posture Map(UPM) is proposed to control the posture of a human-like 3D character. The proposed algorithm quantizes human behaviors without distortion to generate a UPM, and then generates a natural posture by searching the UPM. If necessary, the resulting posture could be compensated with a traditional Cyclic Coordinate Descent (CCD). The proposed method could be applied to produce 3D-character animations based on the key frame method, 3D games and virtual reality.

• Journal of the Society of Disaster Information
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• v.19 no.4
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• pp.897-907
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• 2023

Purpose: In this study, We aim to estimate a untrained person's three postures using a 2D CNN model which is trained with minimal FFT data collected by a 24GHz FMCW radar. Method: In an indoor space, we collected FFT data for three distinct postures (standing, sitting, and lying) from three different individuals. To apply this data to a 2D CNN model, we first converted the collected data into 2D images. These images were then trained using the 2D CNN model to recognize the distinct features of each posture. Following the training, we evaluated the model's accuracy in differentiating the posture features across various individuals. Result: According to the experimental results, the average accuracy of the proposed scheme for the three postures was shown to be a 89.99% and it outperforms the conventional 1D CNN and the SVM schemes. Conclusion: In this study, we aim to estimate any person's three postures using a 2D CNN model and a 24GHz FMCW radar for disastrous situations in indoor. it is shown that the different posture of any persons can be accurately estimated even though his or her data is not used for training the AI model.

• Journal of the Korean Society of Clothing and Textiles
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• v.47 no.2
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• pp.337-352
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• 2023

This study develops a t-shirt design that align bones and balance muscles in order to maintain proper posture using the basic concepts of symmetry. First, theoretical and 3D design studies, existing literature on proper and improper posture, and the basic concepts of symmetry are studied to create the design. Next, the 3D design process applies bilateral, rotational, and scaling symmetries to design the inner lines from the basic application of symmetry. A two-stage design process is used, whereby the strain map and pressure points are analyzed using the CLO virtual clothing software, and the most effective design is determined through virtual testing. The results show that the Y+)( and X+― design, which combines the position and type of inner lines, is the most effective for posture correction and maintenance. Overall, this study helps create a theoretical and practical basis for exploring and understanding basic lines appropriate for the human body, and subsequently, for developing various products that maintain posture more accurately and precisely.

• Smart Media Journal
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• v.12 no.11
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• pp.48-56
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• 2023

The technology of Three-dimensional human posture estimation is used in sports, motion recognition, and special effects of video media. Among various methods for this, multi-view 3D human pose estimation is essential for precise estimation even in complex real-world environments. But Existing models for multi-view 3D human posture estimation have the disadvantage of high order of time complexity as they use 3D feature maps. This paper proposes a method to extend an existing monocular viewpoint multi-frame model based on Transformer with lower time complexity to 3D human posture estimation for multi-viewpoints. To expand to multi-viewpoints our proposed method first generates an 8-dimensional joint coordinate that connects 2-dimensional joint coordinates for 17 joints at 4-vieiwpoints acquired using the 2-dimensional human posture detector, CPN(Cascaded Pyramid Network). This paper then converts them into 17×32 data with patch embedding, and enters the data into a transformer model, finally. Consequently, the MLP(Multi-Layer Perceptron) block that outputs the 3D-human posture simultaneously updates the 3D human posture estimation for 4-viewpoints at every iteration. Compared to Zheng[5]'s method the number of model parameters of the proposed method was 48.9%, MPJPE(Mean Per Joint Position Error) was reduced by 20.6 mm (43.8%) and the average learning time per epoch was more than 20 times faster.

• Journal of Ocean Engineering and Technology
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• v.22 no.5
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• pp.119-125
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• 2008

Musculoskeletal disorders(MSDs) are one of the major issues in shipbuilding industry. Main risk factors of MSDs include manual handling of heavy weight, awkward posture, repetitive tasks, prolonged static muscle contraction, and so on. in this study, Using the three-dimensional digital human modeling and simulation method we made up a worker and work posture on a virtual environment. To verify this simulation we compared both traditional ergonomic analysis on a real worker and digital program analysis on a digital human. And this paper shows that it is possible to reduce the rate of MSDs in the shipbuilding industry because it means we can change poor posture mid surroundings into better ones.

• Journal of KIISE:Software and Applications
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• v.36 no.10
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• pp.836-850
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• 2009

Human posture recognition has attracted tremendous attention in ubiquitous environment, performing arts and robot control so that, recently, many researchers in pattern recognition and computer vision are working to make efficient posture recognition system. However the most of existing studies is very sensitive to human variations such as the rotation or the translation of body. This is why the feature, which is extracted from the feature extraction part as the first step of general posture recognition system, is influenced by these variations. To alleviate these human variations and improve the posture recognition result, this paper presents 3D Star Skeleton and Principle Component Analysis (PCA) based feature extraction methods in the multi-view environment. The proposed system use the 8 projection maps, a kind of depth map, as an input data. And the projection maps are extracted from the visual hull generation process. Though these data, the system constructs 3D Star Skeleton and extracts the rotation invariant feature using PCA. In experimental result, we extract the feature from the 3D Star Skeleton and recognize the human posture using the feature. Finally we prove that the proposed method is robust to human variations.

• Journal of the Korean Society for Computer Game
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• v.31 no.4
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• pp.61-70
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• 2018

In this paper, we propose a synchronized playback method of 3D reference model and video by extracting golf swing information from learner's golf video to precisely compare and analyze each motion in each position and time in the golf swing, and present the implementation result. In order to synchronize the 3D model with the learner's swing video, the learner's golf swing movie is first photographed and relative time information is extracted from the photographed video according to the position of the golf club from the address posture to the finishing posture. Through applying time information from learners' swing video to a 3D reference model that rigs the motion information of a pro-golfer's captured swing motion at 120 frames per second through high-quality motion capture equipment into a 3D model and by synchronizing the 3D reference model with the learner's swing video, the learner can correct or learn his / her posture by precisely comparing his or her posture with the reference model at each position of the golf swing. Synchronized playback can be used to improve the functionality of manually adjusting system for comparing and analyzing the reference model and learner's golf swing. Except for the part where the image processing technology that detects each position of the golf posture is applied, It is expected that the method of automatically extracting the time information of each location from the video and of synchronized playback can be extended to general life sports field.

• Journal of The Korean Society of Integrative Medicine
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• v.8 no.1
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• pp.113-124
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• 2020

Purpose : The purpose of this study was to investigate the effects of exercise intervention combined with 3D visual feedback and motion observation on postural alignment and cerebral cortical activity in subjects with forward head posture (FHP). Methods : The study included 28 participants with FHP, randomly divided into a 3D visual feedback plus motion observation group (n=14) or control group (n=14). The experimental group received corrective exercise combined with 3D visual feedback and motion observation for FHP, three times a week for four weeks. We examined cervical spine radiographs in the lateral standing position with both arms crossed to measure the craniovertebral angle (CVA) and cervical lordosis (CL). Relative alpha (RA) and beta waves (RB) were measured by wireless dry EEG. Results : The CVA value was significantly different between the groups, and the CL value was significantly different only in the experimental group. RA and RB values were not significantly different before and after intervention in the control group. RB values were significantly decreased before and after intervention in the experimental group. Conclusion : Based on the results of this study, we suggest that interventions combined with motion observation and 3D visual feedback may be effective as exercise methods to improve postural alignment and cerebral activity in subjects with FHP. Further research is required to generalize our results on technical supplementation complemented with 3D visual feedback devices.

• Journal of the Korean Society of Costume
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• v.57 no.4 s.113
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• pp.9-17
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• 2007

Somatotype is human body shape and physique type which can be classified not only by the size, but also by the shape or posture of the body. Postural variations in the alignment of the back, shoulder, and neck can have an adverse effect on the fit of garments designed to hang from the shoulders. There have been some previous studies about the lateral upper torso by analyzing photographic measurements. In this study, 3D body scan images were used to classify the side somatotype of upper lateral method even though they are major data in the classification of upper torso. This study focused on following objective.; 1) To apply new and developing technology into the apparel industry analyzing 3D body scan images. 2) To classify upper laterla torso using the data through the new improver technology, 3D body scanner. 3) To propose basic materials for well fitted garments for each type of figure. The test subjects for this study were two hundreds nine female aged 19 years and up who were recruited in Cornell university body scan research team. Seventeen Variables(12 angles, 5 lengths) out of 3D body scan data were measured based on these landmarks and applied to analyze. The result of factor analysis indicated that 6 factors were extracted through factor analysis and orthogonal rotation by the method of Varimax and those factors comprise 62.5% of total variance. And the somatotype of upper body is classified into 3 types of figures according to cluster analysis; Bent forward posture, Straight posture, Swayback posture. Future study could be addressed about the somatotype of body by the age group based on the large database with wide variety of age.