• Proceedings of the KWS Conference
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• 1999.10a
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• pp.51-54
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• 1999

• Proceedings of the Optical Society of Korea Conference
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• 1995.06a
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• pp.105-116
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• 1995

In this paper, we propose a new a new EOST by using the optical JTC(joint transform correlator) as the feature extraction park, because the JTC can adaptively detect the relative displacements of moving targest. Firstly, we derive the BPEJCT(binary phase extraction JTC) which is a phase type JTC and can remove the intracless correlation peaks of the conventional JTC. Then, especially we hardware construction for driving the BPEJTC in real, and with the Kalman target estimation alogorithm, we carried out a target tracking experiment only to show the possibility of real-time implementation of the EOST.

• Journal of Welding and Joining
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• v.9 no.2
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• pp.20-28
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• 1991

The main subject of this study is the construction of an automatic welding system that has the capability to trace the weld seam in GMA welding of lap joints. The system was composed of a vision sensor, moving torch, and personal computer(IBM-PC). In the developed vision sensor, an image was captured by the frame grabber at the time of short circuit during welding. The threshold method was adopted for determining the structured light and the central difference method for detecting the weld joint. And the seam tracing of the torch was performed by using the data regeneration algorithm. In this system using the image at the time of short circuit, weld seam tracking was performed without any relations to arc light and spatters.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.5
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• pp.2346-2362
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• 2016

As one of the most important issues in computer vision and image processing, online object tracking plays a key role in numerous areas of research and in many real applications. In this study, we present a novel tracking method based on the proposed structured sparse representation model, in which the tracked object is assumed to be sparsely represented by a set of object and background templates. The contributions of this work are threefold. First, the structure information of all the candidate samples is utilized by a joint sparse representation model, where the representation coefficients of these candidates are promoted to share the same sparse patterns. This representation model can be effectively solved by the simultaneous orthogonal matching pursuit method. In addition, we develop a tracking algorithm based on the proposed representation model, a discriminative candidate selection scheme, and a simple model updating method. Finally, we conduct numerous experiments on several challenging video clips to evaluate the proposed tracker in comparison with various state-of-the-art tracking algorithms. Both qualitative and quantitative evaluations on a number of challenging video clips show that our tracker achieves better performance than the other state-of-the-art methods.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.642-646
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• 1992

Trajectory tracking control problems are described for a two-link robot manipulator with artificial rubber muscle actuators. Under the assumption that the so-called independent joint control is applied to the control system, the dynamic model for each link is identified as a linear second-order system with time-lag by the step response. Two control laws such as the feedforward and the computed torque control methods, are experimentally applied for controlling the circular trajectory of an actual robot manipulator.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.4
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• pp.411-421
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• 1992

In the conventional track while scan (TWS) system, there are two major functions to be performed : detection and tracking. These two functions are normally designed and optimised independently. So TWS algorithm ignores the available decision features that can help in resolving the plot-to-track association ambiguity. Therefore conventional TWS system cna't track the targets in a densed multi-target environment. This paper presents a new TWS algorithm for multi-target track to solve the existing TWS system problem in clutter environment. The algorithm proposed in this paper is derived by modifying the part of joint probabilistic data association (JPDA) algotithm to get the one to one correspondence instead of multiple correspondence and combined with maneuvering detection logic so that it could also track the low maneuvering targets. Simulations to confirm the performance are done in crossing, parallel and maneuvering target. The proposed algorithm was successfully tracking targets above target situations.

• Proceedings of the KWS Conference
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• 1997.05a
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• pp.133-136
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• 1997

• Proceedings of the KWS Conference
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• 1997.05a
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• pp.125-128
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• 1997

• Proceedings of the KWS Conference
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• 1998.05a
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• pp.204-207
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• 1998

• Clinics in Shoulder and Elbow
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• v.26 no.2
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• pp.126-130
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• 2023

Background: Arm swing plays a role in gait by accommodating forward movement through trunk balance. This study evaluates the biomechanical characteristics of arm swing during gait. Methods: The study performed computational musculoskeletal modeling based on motion tracking in 15 participants without musculoskeletal or gait disorder. A three-dimensional (3D) motion tracking system using three Azure Kinect (Microsoft) modules was used to obtain information in the 3D location of shoulder and elbow joints. Computational modeling using AnyBody Modeling System was performed to calculate the joint moment and range of motion (ROM) during arm swing. Results: Mean ROM of the dominant elbow was 29.7°±10.2° and 14.2°±3.2° in flexion-extension and pronation-supination, respectively. Mean joint moment of the dominant elbow was 56.4±12.7 Nm, 25.6±5.2 Nm, and 19.8±4.6 Nm in flexion-extension, rotation, and abduction-adduction, respectively. Conclusions: The elbow bears the load created by gravity and muscle contracture in dynamic arm swing movement.