• 한국태양에너지학회:학술대회논문집
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• 2009.04a
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• pp.31-36
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• 2009

There have been many solar tracking systems developed for the high accuracy in solar tracking. One of the key components of any motion control system is software. LabVIEW offers an ideal combination of flexibility, ease-of-use and well-integration with other I/O pieces for developing solar tracking system. Real-time solar positions which vary with GPS's data are used simultaneously to control the solar tracker by a chain of operating modes between the open and closed loops. This paper introduces a step by step procedure for the fabrication and performance assessment of a precision solar tracking system. The system developed in this study consists of motion controllers, motor drives, step-motors, feedback devices and application. CRD sensors are applied for the solar tracking system which play a primary role in poor conditions for tracking due to a gear backlash and a strong wind. Mini-dish was used as a concentrator for collecting sun light. The solar position data, in terms of azimuth and elevation, sunrise and sunset times was compared with those of KASI(Korea Astronomy & Space Science Institute). The results presented in this paper demonstrate the accuracy of the present system in solar tracking and utilization.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.1015-1017
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• 2013

Object tracking, in general, is a challenging problem. Difficulties in tracking objects can arise due to abrupt object motion, changing appearance patterns of both the object and the scene, non-rigid object structures, object-to-object and object-to-scene occlusions, and camera motion. Tracking is usually performed in the context of higher-level applications that require the location or the shape of the object in every frame. This paper describes an object tracking system based on active vision with two cameras, into algorithm of single camera tracking system an object active visual tracking and object locked system based on Extend Kalman Filter (EKF) is introduced, by analyzing data from which the next running state of the object can be figured out and after the tracking is performed at each of the cameras, the individual tracks are to be fused (combined) to obtain the final system object track.

• The Journal of Korean Academy of Prosthodontics
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• v.62 no.1
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• pp.82-94
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• 2024

This is a case report of complete mouth rehabilitation in a patient with generalized attrition and loss of posterior support. After analyzing the condition of the temporomandibular joint, multiple implants were placed to restore collapsed occlusion. Fixture/abutment level intraoral scanning was done instead of using conventional impression materials which entail multiple bite registration for cross-mounting. A 'jaw motion tracking'device, 'digital face-bow transfer', and 'double scan technique' which enables duplicating temporary restoration to definitive restoration were used to fabricate definitive prostheses. By using various digital techniques, complete mouth rehabilitation was done with minimal chair time in a patient with unstable occlusion.

• Journal of Korea Multimedia Society
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• v.23 no.1
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• pp.15-23
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• 2020

Recently, the increase in the elderly population due to an aging society has led to a relative increase in senile diseases such as vascular dementia or Alzheimer's disease, and the social burden for rehabilitation has increased. In addition, studies have been conducted for the risk assessment and prevention of musculoskeletal disorders. The purpose of this study is to suggest a system that can be used to help with dementia prevention training by tracking the movement of motion and virtual reality contents for the risk factors of musculoskeletal disorders of the elderly. We propose a training method for preventing dementia through musculoskeletal motion analysis algorithm and virtual reality content. Through motion recognition algorithm based on motion region design, we will track and analyze the moving radius of the target joint. The purpose of this study is to calculate and evaluate scores based on the time to accomplish the goals on virtual reality contents for the prevention of musculoskeletal disorders and the support of dementia prevention training, and the degree of difficulty, and to analyze the correlation between the results of performing K-MMSE and VR contents.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.1
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• pp.60-65
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• 2012

This paper presents a method for occluded object based motion estimation and tracking system in dynamic image sequences using particle filter with 3D reconstruction. A unique characteristic of this study is its ability to cope with partial occlusion based continuous motion estimation using particle filter inspired from the mirror neuron system in human brain. To update a prior knowledge about the shape or motion of objects, firstly, fundamental 3D reconstruction based occlusion tracing method is applied and object landmarks are determined. And optical flow based motion vector is estimated from the movement of the landmarks. When arbitrary partial occlusions are occurred, the continuous motion of the hidden parts of object can be estimated by particle filter with optical flow. The resistance of the resulting estimation to partial occlusions enables the more accurate detection and handling of more severe occlusions.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.6
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• pp.605-612
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• 2015

Three dimensional (3D) position determination and motion recognition using a 3D depth sensor camera are applied to a developed penguin-shaped robot, and its validity and closeness are investigated. The robot is equipped with an Asus Xtion Pro Live as a 3D depth camera, and a sound module. Using the skeleton information from the motion recognition data extracted from the camera, the robot is controlled so as to follow the typical three mode-reactions formed by the operator's gestures. In this study, the extraction of skeleton joint information using the 3D depth camera is introduced, and the tracking performance of the operator's motions is explained.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.2
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• pp.39-49
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• 2002

This paper proposes the MAWUPC (Motion Adaptive Weighted Unmatched Pixel Count) algorithm to track multiple objects of similar color The MAWUPC algorithm has the new method that combines color and motion effectively. We apply the MAWUPC algorithm to face and hand tracking against complex background in an image sequence captured by using single camera. The MAWUPC algorithm is an improvement of previously proposed AWUPC (Adaptive weighted Unmatched Pixel Count) algorithm based on the concept of the Moving Color that combines effectively color and motion information. The proposed algorithm incorporates a color transform for enhancing a specific color, the UPC(Unmatched Pixel Count) operation for detecting motion, and the discrete Kalman filter for reflecting motion. The proposed algorithm has advantages in reducing the bad effect of occlusion among target objects and, at the same time, in rejecting static background objects that have a similar color to tracking objects's color. This paper shows the efficiency of the proposed MAWUPC algorithm by face and hands tracking experiments for several image sequences that have complex backgrounds, face-hand occlusion, and hands crossing.

• Korean Journal of Remote Sensing
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• v.34 no.6_2
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• pp.1215-1227
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• 2018

Sea ice motion is an important factor for assessing change of sea ice because the motion affects to not only regional distribution of sea ice but also new ice growth and thickness of ice. This study presents an application of multi-temporal high-resolution optical satellites images obtained from Korea Multi-Purpose Satellite-2 (KOMPSAT-2) and Korea Multi-Purpose Satellite-3 (KOMPSAT-3) to measure sea ice motion using SIFT (Scale-Invariant Feature Transform), SURF (Speeded Up Robust Features) and ORB (Oriented FAST and Rotated BRIEF) feature tracking techniques. In order to use satellite images from two different sensors, spatial and radiometric resolution were adjusted during pre-processing steps, and then the feature tracking techniques were applied to the pre-processed images. The matched features extracted from the SIFT showed even distribution across whole image, however the matched features extracted from the SURF showed condensed distribution of features around boundary between ice and ocean, and this regionally biased distribution became more prominent in the matched features extracted from the ORB. The processing time of the feature tracking was decreased in order of SIFT, SURF and ORB techniques. Although number of the matched features from the ORB was decreased as 59.8% compared with the result from the SIFT, the processing time was decreased as 8.7% compared with the result from the SIFT, therefore the ORB technique is more suitable for fast measurement of sea ice motion.

• Journal of Korea Multimedia Society
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• v.15 no.3
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• pp.336-344
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• 2012

As an important part of the Computer Vision, the object recognition and tracking function has infinite possibilities range from motion recognition to aerospace applications. One of methods to improve accuracy of the object recognition, are uses colors which have robustness of orientation, scale and occlusion. Computational cost for extracting features can be reduced by using color. Also, for fast object recognition, predicting the location of the object recognition in a smaller area is more effective than lowering accuracy of the algorithm. In this paper, we propose a method that uses SURF descriptors which applied with color model for improving recognition accuracy and combines with Kalman filter which is Motion estimation algorithm for fast object tracking. As a result, the proposed method classified objects which have same patterns with different colors and showed fast tracking results by performing recognition in ROI which estimates future motion of an object.

• 전자공학회논문지 IE
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• v.43 no.2
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• pp.54-62
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• 2006

In this paper, a new stereo object tracking system using the disparity motion vector is proposed. In the proposed method, the time-sequential disparity motion vector can be estimated from the disparity vectors which are extracted from the sequence of the stereo input image pair and then using these disparity motion vectors, the area where the target object is located and its location coordinate are detected from the input stereo image. Basing on this location data of the target object, the pan/tilt embedded in the stereo camera system can be controlled and as a result, stereo tracking of the target object can be possible. From some experiments with the 2 frames of the stereo image pairs having $256\times256$ pixels, it is shown that the proposed stereo tracking system can adaptively track the target object with a low error ratio of about 3.05 % on average between the detected and actual location coordinates of the target object.