• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.12
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• pp.3315-3337
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• 2012

Crowded scenes analysis is a challenging topic in computer vision field. How to detect diverse motion patterns in crowded scenarios from videos is the critical yet hard part of this problem. In this paper, we propose a novel approach to mining motion patterns by utilizing motion information during both long-term period and short interval simultaneously. To capture long-term motions effectively, we introduce Motion History Image (MHI) representation to access to the global perspective about the crowd motion. The combination of MHI and optical flow, which is used to get instant motion information, gives rise to discriminative spatial-temporal motion features. Benefitting from the robustness and efficiency of the novel motion representation, the following motion pattern mining is implemented in a completely unsupervised way. The motion vectors are clustered hierarchically through automatic hierarchical clustering algorithm building on the basis of graphic model. This method overcomes the instability of optical flow in dealing with time continuity in crowded scenes. The results of clustering reveal the situations of motion pattern distribution in current crowded videos. To validate the performance of the proposed approach, we conduct experimental evaluations on some challenging videos including vehicles and pedestrians. The reliable detection results demonstrate the effectiveness of our approach.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.2
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• pp.121-130
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• 2012

This paper proposes an intuitive real-time robot control system using human body movement. Recently, it has been developed that motion generation for humanoid robots with reflecting human body movement, which is measured by a motion capture. However, in the existing studies about robot control system by human body movement, the detailed structure information of a robot, for example, degrees of freedom, the range of motion and forms, must be examined in order to calculate inverse kinematics. In this study, we have proposed Associative Motion Generation as humanoid robot motion generation method which does not need the detailed structure information. The associative motion generation system is composed of two neural networks: nonlinear principal component analysis and Jordan recurrent neural network, and the associative motion is generated with the following three steps. First, the system learns the correspondence relationship between an indication and a motion using training data. Second, associative values are extracted for associating a new motion from an unfamiliar indication using nonlinear principal component analysis. Last, the robot generates a new motion through calculation by Jordan recurrent neural network using the associative values. In this paper, we propose a real-time humanoid robot control system based on Associative Motion Generation, that enables user to control motion intuitively by human body movement. Through the task processing and subjective evaluation experiments, we confirmed the effective usability and affective evaluations of the proposed system.

• Journal of The Korean Society of Integrative Medicine
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• v.7 no.2
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• pp.59-67
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• 2019

Purpose : The purpose of this study was to analyze the dynamic range of motion (ROM) of pelvic and translation of center of mass (COM) when wearing different shoe insole lifts according to leg length discrepancy (LLD) during free speed gait. Methods : Thirty-five healthy adults were participated in this study. Kinematic data were collected using a Vicon motion capture system. Reflective and cluster 40 markers attached to participants lower extremities and were asked to walk in a 6 m gait way under three different shoe lift conditions (without any insole, 1 cm insole, and 2 cm insole). The pelvic ROM and COM translation in three planes were sorted using a Nexus software, and a Visual3D motion analysis software was used to coordinate all kinematic data. Results : There were significantly increased maximal pelvic elevation and total pelvic range in coronal plane when wearing a standard shoe with 2 cm insole lift during gait (p<.05). When wearing a standard shoe with 2 cm insole lift, the total range of the pelvic segment were significantly different in all three motion planes (p<.05). Conclusion : Although LLD of less than 2 cm develops abnormal movement pattern of the pelvis and may cause of musculoskeletal diseases such as low back pain, hip and knee joint osteoarthritis, therefore intensive various physical therapy interventions for LLD are needed.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.6
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• pp.181-190
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• 2021

Sports activities conducted by multiple people are difficult to proceed in a situation where a widespread epidemic such as COVID-19 is spreading, and this causes a lack of physical activity in modern people. This problem can be overcome by using online exercise contents, but it is difficult to check detailed postures such as during face-to-face exercise. In this study, we present a model that detects posture and tracks movement using IT system for better non-face-to-face exercise content management. The proposed motion tracking model defines a body model with reference to motion analysis methods widely used in physical education and defines posture and movement accordingly. Using the proposed model, it is possible to recognize and analyze movements used in exercise, know the number of specific movements in the exercise program, and detect whether or not the exercise program is performed. In order to verify the validity of the proposed model, we implemented motion tracking and exercise program tracking programs using Azure Kinect DK, a markerless motion capture device. If the proposed motion tracking model is improved and the performance of the motion capture system is improved, more detailed motion analysis is possible and the number of types of motions can be increased.

• Advances in biomechanics and applications
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• v.1 no.4
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• pp.269-277
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• 2014

In skin-marker based motion analysis, knee translation measurement is highly dependent on a pre-selected reference point (functional center) on each segment determined by the location of anatomical landmarks. However, the placement of skin markers on palpable anatomical landmarks (i.e., femoral epicondyles) has limited reproducibility. Thus, it produces large variances in knee translation measurement among different subjects, as well as across studies. In order improve the repeatability of knee translation measurement, in this study an optimization method was introduced, by which the femoral functional center was numerically determined. At that point the knee anteroposterior translation during the stance phase of walking was minimized. This new method was tested on 30 healthy subjects during walking in gait lab with motion capture system. Using this new method, the impact of skin marker position (at anatomical landmarks) on the knee translation measurement has been minimized. In addition, the ranges of anteroposterior knee translations during stance phase were significantly (p<0.001) smaller than those measured by conventional method which relies on a pre-selected functional center ($11.1{\pm}3.5mm$ vs. $19.9{\pm}5.5mm$). The results of anteroposterior translation using this new method were very close to a previously reported knee translation (12.4 mm) from dual fluoroscopic imaging technique. Moreover, this new method increased the reproducibility of knee translation measurement by 50%.

• Journal of Navigation and Port Research
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• v.48 no.2
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• pp.116-124
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• 2024

Automatic docking of small planing ship is a critical aspect of maritime operations, requiring accurate prediction of motion states to ensure safe and efficient maneuvers. This study investigates the use of Artificial Neural Network (ANN) to predict motion state of a small planing ship to enhance navigation automation in port environments. To achieve this, simulation tests were conducted to control a small planing ship while docking at various heading angles in calm water and in waves. Comprehensive analysis of the ANN-based predictive model was conducted by training and validation using data from various docking situations to improve its ability to accurately capture motion characteristics of a small planing ship. The trained ANN model was used to predict the motion state of the small planning ship based on any initial motion state. Results showed that the small planing ship could dock smoothly in both calm water and waves conditions, confirming the accuracy and reliability of the proposed method for prediction. Moreover, the ANN-based prediction model can adjust the dynamic model of the small planing ship to adapt in real-time and enhance the robustness of an automatic positioning system. This study contributes to the ongoing development of automated navigation systems and facilitates safer and more efficient maritime transport operations.

• The Journal of the Korea Contents Association
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• v.20 no.5
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• pp.69-78
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• 2020

K/DA is a K-pop virtual idol based on the game character. This study analyzed the creation process, characteristics and existential meaning of virtual idols from the perspective of Pataphysics. K/DA is a character with both characteristics of game character and K-pop girl group. Also, virtual character and real idol share the body through motion capture and augmented reality(AR). As a result, K/DA crosses virtual and reality, and at the same time becomes a pataphysical subject that does not belong to either virtual or reality. K/DA is suggested a third zone where digital subjects will be located in the future.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.436-442
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• 2016

There are a lot of sports when you left the victory and the defeat of the match the referee subjective judgment. In particular, TaeKwonDo pumse How accurate a given action? Is important. Objectively evaluate the subjective opinion of victory and defeat in a sporting event and the technology to keep as evidence is required. This study was implemented a system for recognizing Taekwondo executed through the number of motion recognition device. Step Sensor also used to detect a user's location. This study evaluated the rate matching the standard gesture data and the motion data. Through multiple gesture recognition equipment was more accurate assessment of the Taekwondo action.

• Korean Journal of Computational Design and Engineering
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• v.17 no.1
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• pp.62-70
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• 2012

This paper proposes a novel discomfort assessment method for truck ingress and egress motions based on the maximum-voluntary-contraction (MVC) ratios of muscles obtained by biomechanical analysis of human musculoskeletal models. In this study, a human motion to enter and exit a truck cabin with different types and heights of footsteps is first measured using an optical motion capture system and load sensors. Next, in a biomechanical analysis system, a human musculoskeletal model with contacting conditions on footsteps and handles is modeled, and then joint torques and muscles forces are calculated by inverse dynamics of the musculoskeletal model with the motion data. Finally, the MVC ratios for the muscles are calculated and their statistical values are used as the measure of discomfort. To ensure the feasibility of our method, subjective discomfort levels have been investigated through the participants' experiments and questionnaires and compared to the results of our method. Comparing to the existing methods based on joint angles or torques, our approach provide a more essential criterion for discomfort because it is based on the muscle contraction by which an active human motion is basically generated.

• Earthquakes and Structures
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• v.20 no.1
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• pp.97-107
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• 2021

A comprehensive study on seismic performance of wood frame building in hilly regions is presented. Specifically, seismic fragility assessment of a typical wood frame building at various locations of the northeast region of India are demonstrated. A three-dimensional simplified model of the wood frame building is developed with due consideration to nonlinear behaviour of shear walls under lateral loads. In doing so, a trilinear model having improved capability to capture the force-deformation behaviour of shear walls including the strength degradation at higher deformations is proposed. The improved capability of the proposed model to capture the force-deformation behaviour of shear wall is validated by comparing with the existing experimental results. The structural demand values are obtained from nonlinear time history analysis (NLTHA) of the three-dimensional wood frame model considering the effect of uncertainty due to record to record variation of ground motions and structural parameters as well. The ground motion bins necessary for NLTHA are prepared based on the identified hazard level from probabilistic seismic hazard analysis of the considered locations. The maximum likelihood estimates of the lognormal fragility parameters are obtained from the observed failure cases and the seismic fragilities corresponding to different locations are estimated accordingly. The results of the numerical study show that the wood frame constructions commonly found in the region are likely to suffer minor cracking or damage in the shear walls under the earthquake occurrence corresponding to the estimated seismic hazard level; however, poses negligible risk against complete collapse of such structures.