• Journal of Institute of Control, Robotics and Systems
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• v.20 no.8
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• pp.789-794
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• 2014

This paper presents some real performance of two typical bilateral teleoperation benchmark tasks: peg-in-hole and surface tracking tasks. The tasks are performed by an energy-bounding algorithm in the master control and position-based impedance algorithm in the slave control. Performance is analyzed for the position-force tracking capabilities from free space motion to surface contacting motion. In addition, preliminary user performance is evaluated by measuring the completion time and maximum/average contact forces. The quality of the measured performance is also compared with that of other existing approaches.

• ETRI Journal
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• v.30 no.2
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• pp.338-340
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• 2008

In this letter, we propose a novel approach to detecting and tracking apartment buildings for the development of a video-based navigation system that provides augmented reality representation of guidance information on live video sequences. For this, we propose a building detector and tracker. The detector is based on the AdaBoost classifier followed by hierarchical clustering. The classifier uses modified Haar-like features as the primitives. The tracker is a motion-adjusted tracker based on pyramid implementation of the Lukas-Kanade tracker, which periodically confirms and consistently adjusts the tracking region. Experiments show that the proposed approach yields robust and reliable results and is far superior to conventional approaches.

• Radiation Oncology Journal
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• v.26 no.4
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• pp.263-270
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• 2008

Purpose: This study aimed to quantitatively measure the movement of tumors in real-time and evaluate the treatment accuracy, during the treatment of a liver tumor patient, who underwent radiosurgery with a Synchrony Respiratory motion tracking system of a robot CyberKnife. Materials and Methods: The study subjects included 24 liver tumor patients who underwent CyberKnife treatment, which included 64 times of treatment with the Synchrony Respiratory motion tracking system ($Synchrony^{TM}$). The treatment involved inserting 4 to 6 acupuncture needles into the vicinity of the liver tumor in all the patients using ultrasonography as a guide. A treatment plan was set up using the CT images for treatment planning uses. The position of the acupuncture needle was identified for every treatment time by Digitally Reconstructed Radiography (DRR) prepared at the time of treatment planning and X-ray images photographed in real-time. Subsequent results were stored through a Motion Tracking System (MTS) using the Mtsmain.log treatment file. In this way, movement of the tumor was measured. Besides, the accuracy of radiosurgery using CyberKnife was evaluated by the correlation errors between the real-time positions of the acupuncture needles and the predicted coordinates. Results: The maximum and the average translational movement of the liver tumor were measured 23.5 mm and $13.9{\pm}5.5\;mm$, respectively from the superior to the inferior direction, 3.9 mm and $1.9{\pm}0.9mm$, respectively from left to right, and 8.3 mm and $4.9{\pm}1.9\;mm$, respectively from the anterior to the posterior direction. The maximum and the average rotational movement of the liver tumor were measured to be $3.3^{\circ}$ and $2.6{\pm}1.3^{\circ}$, respectively for X (Left-Right) axis rotation, $4.8^{\circ}$ and $2.3{\pm}1.0^{\circ}$, respectively for Y (Crania-Caudal) axis rotation, $3.9^{\circ}$ and $2.8{\pm}1.1^{\circ}$, respectively for Z (Anterior-Posterior) axis rotation. In addition, the average correlation error, which represents the treatment's accuracy was $1.1{\pm}0.7\;mm$. Conclusion: In this study real-time movement of a liver tumor during the radiosurgery could be verified quantitatively and the accuracy of the radiosurgery with the Synchrony Respiratory motion tracking system of robot could be evaluated. On this basis, the decision of treatment volume in radiosurgery or conventional radiotherapy and useful information on the movement of liver tumor are supposed to be provided.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1055-1058
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• 2003

The robustness and reliability of vision algorithms is the key issue in robotic research and industrial applications. In this paper robust real time visual tracking in complex scene is considered. A common approach to increase robustness of a tracking system is the use of different model (CAD model etc.) known a priori. Also fusion or multiple features facilitates robust detection and tracking of objects in scenes of realistic complexity. Voting-based fusion of cues is adapted. In voting. a very simple or no model is used for fusion. The approach for this algorithm is tested in a 3D Cartesian robot which tracks a toy vehicle moving along 3D rail, and the Kalman filter is used to estimate the motion parameters. namely the system state vector of moving object with unknown dynamics. Experimental results show that fusion of cues and motion estimation in a tracking system has a robust performance.

• Journal of Broadcast Engineering
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• v.19 no.6
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• pp.942-956
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• 2014

This paper proposes a real-time hand pose tracking method using a monocular RGB camera. Hand tracking has high ambiguity since a hand has a number of degrees of freedom. Thus, to reduce the ambiguity the proposed method adopts the step-by-step estimation scheme: a palm pose estimation, a finger yaw motion estimation, and a finger pitch motion estimation, which are performed in consecutive order. Assuming a hand to be a plane, the proposed method utilizes a planar hand model, which facilitates a hand model regeneration. The hand model regeneration modifies the hand model to fit a current user's hand, and improves robustness and accuracy of the tracking results. The proposed method can work in real-time and does not require GPU-based processing. Thus, it can be applied to various platforms including mobile devices such as Google Glass. The effectiveness and performance of the proposed method will be verified through various experiments.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.1-11
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• 2004

In this paper we proposed a hierarchical ASM for real-time tracking of non-rigid objects. For tracking an object we used ASM for estimating object contour possibly with occlusion. Moreover, to reduce the processing time we used hierarchical approach for real-time tacking. In the next frame we estimated the initial feature point by using Kalman filter. We also added block matching algorithm for increasing accuracy of the estimation. The proposed hierarchical, prediction-based approach was proven to out perform the exiting non-hierarchical, non-prediction methods.

• Korean Journal of Applied Biomechanics
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• v.29 no.1
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• pp.1-8
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• 2019

Objective: The purpose of this study was to confirm that the cross-country ski sprint course in PyeongChang, where the 2018 Winter Olympics course was to utilize wearable devices equipped with inertial measurement unit (IMU), global positioning system (GPS) and heart rates sensor. Method: For the data collection, two national level cross-country (XC) skiers performed classic technique on the entire sprint course. We analyzed cycle characteristics, range of motion on double poling (DP) technique, average velocity, and displacement of 3 points according to the terrain. Results: The absolute cycle time gradually decreased during starting, middle and finish sections. While the length of the DP increased and the heart rates tended to increase for men skier. In addition, the results indicated that range of motion of knee joint during starting and finish section decreased more than middle section. The errors of latitude and longitude data collected through GPS were within 3 m from 3 points. Conclusion: Through the first case study in Korea, which analyzed the location and condition of XC skiers in the entire sprint course in real time, confirmed that feedback was available in the field using various wearable sensors.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.740-745
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• 2003

Motion tracking and object segmentation are the most fundamental and critical problems in vision tasks suck as motion analysis. An active contour model, snake, was developed as a useful segmenting and tracking tool for rigid or non-rigid objects. Snake is designed no the basis of snake energies. Segmenting and tracking can be executed successfully by energy minimization. In this research, two new paradigms for segmentation and tracking are suggested. First, because the conventional method uses only intensity information, it is difficult to separate an object from its complex background. Therefore, a new energy and design schemes should be proposed for the better segmentation of objects. Second, conventional snake can be applied in situations where the change between images is small. If a fast moving object exists in successive images, conventional snake will not operate well because the moving object may have large differences in its position or shape, between successive images. Snakes's nodes may also fall into the local minima in their motion to the new positions of the target object in the succeeding image. For robust tracking, the condensation algorithm was adopted to control the parameters of the proposed snake model called "adaptive color snake model(SCSM)". The effectiveness of the ACSM is verified by appropriate simulations and experiments.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.38
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• pp.13.1-13.12
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• 2016

Background: Mandibular motion tracking system (ManMoS) has been developed for orthognathic surgery. This article aimed to introduce the ManMoS and to examine the accuracy of this system. Methods: Skeletal and dental models are reconstructed in a virtual space from the DICOM data of three-dimensional computed tomography (3D-CT) recording and the STL data of 3D scanning, respectively. The ManMoS uniquely integrates the virtual dento-skeletal model with the real motion of the dental cast mounted on the simulator, using the reference splint. Positional change of the dental cast is tracked by using the 3D motion tracking equipment and reflects on the jaw position of the virtual model in real time, generating the mixed-reality surgical simulation. ManMoS was applied for two clinical cases having a facial asymmetry. In order to assess the accuracy of the ManMoS, the positional change of the lower dental arch was compared between the virtual and real models. Results: With the measurement data of the real lower dental cast as a reference, measurement error for the whole simulation system was less than 0.32 mm. In ManMoS, the skeletal and dental asymmetries were adequately diagnosed in three dimensions. Jaw repositioning was simulated with priority given to the skeletal correction rather than the occlusal correction. In two cases, facial asymmetry was successfully improved while a normal occlusal relationship was reconstructed. Positional change measured in the virtual model did not differ significantly from that in the real model. Conclusions: It was suggested that the accuracy of the ManMoS was good enough for a clinical use. This surgical simulation system appears to meet clinical demands well and is an important facilitator of communication between orthodontists and surgeons.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.798-802
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• 2003

The robustness and reliability of vision algorithms is the key issue in robotic research and industrial applications. In this paper, the robust real time visual tracking in complex scene is considered. A common approach to increase robustness of a tracking system is to use different models (CAD model etc.) known a priori. Also fusion of multiple features facilitates robust detection and tracking of objects in scenes of realistic complexity. Because voting is a very simple or no model is needed for fusion, voting-based fusion of cues is applied. The approach for this algorithm is tested in a 3D Cartesian robot which tracks a toy vehicle moving along 3D rail, and the Kalman filter is used to estimate the motion parameters, namely the system state vector of moving object with unknown dynamics. Experimental results show that fusion of cues and motion estimation in a tracking system has a robust performance.