• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.947-948
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• 2006

This paper proposes a robust posture stabilization control method for wheeled mobile robots. To solve the robust posture stabilization, we introduce reference generation mode, reference tracking mode, and reference regulation mode. In reference generation mode, a kinematic time-invariant controller is used to generate the reference trajectory which starts from the initial posture of the actual robot to the desired posture. In reference tracking mode, a sliding mode position controller is employed in such a way that the actual robot can follow the reference trajectory in the desired forward or backward moving direction, even in the presence of the disturbances in the dynamics. In reference regulation mode, a sliding mode heading direction controller is used such that the actual robot can maintain the desired posture against the disturbances. In this way, robust posture stabilization can be achieved at almost all global regions.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.10
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• pp.890-897
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• 2002

This paper deals with the reduction of trajectory tracking error by changing the initial postures of a biped robot. Gait of a biped robot depends on the constraints of mechanical kinematics and the initial states including the posture. Also the dynamic walking stability in a biped robot system is analyzed by zero moment point(ZMP) among the stabilization indices. Path trajectory, in which knee joint is bent forward like human's cases, is applied to most cases considered with above conditions. A new initial posture, which is similar to bird's gait, is proposed to decrease trajectory tracking error and it is verified through real experimental results.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.411-417
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• 2009

We proposed a robust body part tracking system for intelligent environment that will not limit freedom of users. Unlike any previous gesture recognizer, we upgraded the generality of the system by creating the ability the ability to recognize details, such as, the ability to detect the difference between long sleeves and short sleeves. For the precise each body part tracking, we obtained the image of hands, head, and feet separately from a single camera, and when detecting each body part, we separately chose the appropriate feature for certain parts. Using a calibrated camera, we transferred 2D detected body parts into the 3D posture. In the experimentation, this system showed advanced hand tracking performance in real time(50fps).

• Journal of Advanced Marine Engineering and Technology
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• v.17 no.5
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• pp.44-53
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• 1993

In this paper, we discuss on the control algorithm to make the wheeled inverse pendulum type mobile robot move in two dimensional plane. The robot considered in this paper has two independently driven wheels in same axel which suport and move it-self, and is assumed to have the fyro type sensor to know the inclination algle of the body and rotary encoders to know wheel's rotation angular velocity. The control algorithm is divided into three parts. The first part is for the posture and velocity control for forward-backward direction, the second is the steering control, and the last part is for the control of total system to track the given trajectory. We handle the running velocity control of the robot as part of the posture control to keep the balance because the posture relates deeply with the velocity and can be controlled by the velocities of the wheels. The control problem is analyzed as the tracking control, and the controller is realized with the state feedback and feed-forward of the reference velocity. Constructing the control system which contained one intergrator in forward path, we also realized the control system without observer for the estimation of the accumulated errors in the inclination angle of the body. To prevent the robot from being unstable state by sudden variation of the reference velocity when it starts and stops, or changes velocity, the reference velocity of which acceleration is slowly changing, is ordered to the robot. To control its steering, we give the different reference velocities for both wheels which are calculated from the desired angular velocity of the body. Finally, we presents the experimental results of the experimental robot Yamabico Kurara in which the proposed control algorithm had been implemented.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.115-125
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• 2023

This paper relates to the development of CCTV camera posture calibration algorithm that can simultaneously collect traffic information such as traffic volume and speed in the state of view of the CCTV camera set for traffic monitoring. The developed autonomous posture calibration algorithm uses vehicle recognition and tracking techniques to identify the road, and automatically determines the angle of view for the operator's traffic surveillance and traffic information collection. To verify the performance of the proposed algorithm, a CCTV installed on site was used, and the results of the angle of view automatically calculated by the autonomous posture calibration algorithm for the angle of view set for traffic surveillance and traffic information collection were compared.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.147-156
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• 2024

This paper introduces the design of a turtle neck posture correction and prevention system for users of digital devices for a long time. The number of forward head posture patients in Korea increased by 13% from 2018 to 2021, and has not yet improved according to the latest statistics at the present time. Because of the nature of the disease, prevention is more important than treatment. Therefore, in this paper, we designed a system based on built-camera in most laptops to increase the accessiblility of the system, and utilize the features such as Pose Estimation, Face Landmarks Detection, Iris Tracking, and Depth Estimation of Google Mediapipe to prevent the need to produce artificial intelligence models and allow users to easily prevent forward head posture.

• Journal of Korea Multimedia Society
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• v.14 no.12
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• pp.1517-1527
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• 2011

This paper presents a motion capture based rehabilitation training system for a lower-limb paretic patient. The system evaluates the rehabilitation status of the patient by using the bend posture of the knees and the weight balance of the body. The posture of both legs is captured with a single camera using the planar mirror. The weight distribution is obtained by the Wii Balance Board. Self-occlusion problem in the tracking of the legs is resolved by using k-nearest neighbor based clustering with body symmetry and local-linearity of the posture data. To do this, we present data normalization and its symmetric property in the normalized vector space.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.289-290
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• 2020

본 논문에서는 오픈 소스인 openpose skeleton tracking 기술을 이용하여 특정 운동 동작을 영상처리 기술과 딥러닝 기술로 인체 자세에 대해서 인지와 상황 판단하여 운동 동작에 대한 인식 결과를 도출할 수 있다. 먼저 입력받은 영상을 전달받아서 딥러닝 인식 시스템를 통해 인식 결과을 추출한 뒤 비교, 분석한 후에 사전 등록된 운동 동작 명칭으로 화면에 표시하여 이용자가 정확한 동작을 취할 수 있도록 지도하는 데 활용할 수 있다. 또한, 이 기술은 행동 인식부터 얼굴 인식, 손동작 인식 등에 다양하게 활용할 수 있다.

• Journal of Internet Computing and Services
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• v.7 no.1
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• pp.65-74
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• 2006

Human tracking is a requirement for the advanced human-computer interface (HCI), This paper proposes a method which uses a component-based human model, detects body parts, estimates human postures, and animates an avatar, Each body part consists of color, connection, and location information and it matches to a corresponding component of the human model. For human tracking, the 2D information of human posture is used for body tracking by computing similarities between frames, The depth information is decided by a relative location between components and is transferred to a moving direction to build a 2-1/2D human model. While each body part is modelled by posture and directions, the corresponding component of a 3D avatar is rotated in 3D using the information transferred from the human model. We achieved 90% tracking rate of a test video containing a variety of postures and the rate increased as the proposed system processed more frames.

• International journal of advanced smart convergence
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• v.4 no.2
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• pp.20-28
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• 2015

In this paper, we propose an effective tracking algorithm with an appearance model based on features extracted from a video frame with posture variation and camera view point adaptation by employing the non-adaptive random projections that preserve the structure of the image feature space of objects. The existing online tracking algorithms update models with features from recent video frames and the numerous issues remain to be addressed despite on the improvement in tracking. The data-dependent adaptive appearance models often encounter the drift problems because the online algorithms does not get the required amount of data for online learning. So, we propose an effective tracking algorithm with an appearance model based on features extracted from a video frame.