• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.11
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• pp.47-55
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• 2012

In this paper, we propose a method to reconstruct accurate 3D shape object by using multi-view images which are disturbed by motion blur. In multi-view deblurring, more precise PSF estimation can be done by using the geometric relationship between multi-view images. The proposed method first estimates initial 2D PSFs from individual input images. Then 3D PSF candidates are projected on the input images one by one to find the best one which are mostly consistent with the initial 2D PSFs. 3D PSF consists with direction and density and it represents the 3D trajectory of object motion. 야to restore 3D shape by using multi-view images computes the similarity map and estimates the position of 3D point. The estimated 3D PSF is again projected to input images and they replaces the intial 2D PSFs which are finally used in image deblurring. Experimental result shows that the quality of image deblurring and 3D reconstruction improves significantly compared with the result when the input images are independently deblurred.

• Journal of Korea Multimedia Society
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• v.13 no.5
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• pp.663-673
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• 2010

As a tool used for video maintenance, Video segmentation divides videos in hierarchical and structural manner. This technique can be considered as a core technique that can be applied commonly for various applications such as indexing, abstraction or retrieval. Conventional video segmentation used adaptive threshold to split video by calculating difference between consecutive frames and threshold value in window with fixed size. In this case, if the time difference between occurrences of cuts is less than the size of a window or there is much difference in neighbor feature, accurate detection is impossible. In this paper, Improved Adaptive threshold algorithm which enables determination of window size according to video format and reacts sensitively on change in neighbor feature is proposed to solve the problems above. Post-Processing method for decrement in error caused by camera flash and fast movement of large objects is applied. Evaluation result showed that there is 3.7% improvement in performance of detection compared to conventional method. In case of application of this method on modified video, the result showed 95.5% of reproducibility. Therefore, the proposed method is more accurated compared to conventional method and having reproducibility even in case of various modification of videos, it is applicable in various area as a video maintenance tool.

• Korean Journal of Applied Biomechanics
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• v.19 no.4
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• pp.779-791
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• 2009

The purpose of this study is to develop a program that computes the position of the instantaneous center of rotation while an object moves in a circular motion. For this study, a mathematical algorithm was developed and implemented on the experimental data. Data for pitching (40m carry) and putting (4m) strokes were obtained from a skilled female golfer. A computer program (Centering 1.0) calculated the experimental data and found the radius of the instantaneous center of rotation. When the data were taken broadly, the program produced an error distance of radius. When the data were divided gradually, the program produced a very close instantaneous center of rotation. On comparing pitching and putting strokes, putting was found to have a greater radius than pitching. The instantaneous centers of rotation of putting were not in the golfer's body rather, they were 3m away from the club head. The Centering 1.0 program can calculate the instantaneous center of rotation with at least three sets of experimental data.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.2
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• pp.89-98
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• 2009

In the field of computer vision, image mosaicking is a common method for effectively increasing restricted the field of view of a camera by combining a set of separate images into a single seamless image. Image mosaicking based on feature points has recently been a focus of research because of simple estimation for geometric transformation regardless distortions and differences of intensity generating by motion of a camera in consecutive images. Yet, since most feature-point matching algorithms extract feature points using gray values, identifying corresponding points becomes difficult in the case of changing illumination and images with a similar intensity. Accordingly, to solve these problems, this paper proposes a method of image mosaicking based on feature points using color information of images. Essentially, the digital values acquired from a digital color camera are converted to values of a virtual camera with distinct narrow bands. Values based on the surface reflectance and invariant to the chromaticity of various illuminations are then derived from the virtual camera values and defined as color-invariant values invariant to changing illuminations. The validity of these color-invariant values is verified in a test using a Macbeth Color-Checker under simulated illuminations. The test also compares the proposed method using the color-invariant values with the conventional SIFT algorithm. The accuracy of the matching between the feature points extracted using the proposed method is increased, while image mosaicking using color information is also achieved.

• Journal of The Korean Association For Science Education
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• v.39 no.1
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• pp.73-88
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• 2019

The purpose of this study is to explore elementary teachers' difficulties on teaching science by analyzing questions that have been posted for a long time in an autonomous online teacher community named Indischool. For this purpose, 409 question postings(the 2007 and 2009 revised curriculum, third to sixth grade) were analyzed using the framework for analyzing questions about elementary teachers' science teaching(modified from Alake-Tuenter et al., 2013). The study revealed that there were more science-SMK questions than science-PCK questions, and most of the questions were 'about lenses' and 'in 2014 and 2015, when the curriculum was changing from the 2007 to the 2009 revised curriculum'. The long-standing difficulties in science-SMK were 'an application of facts and concepts in lenses' and 'an unexpected experimental error in electricity'. In particular, there are the principle of transparent cup-shaped objects acting as lenses, the process of image formation by convex lenses, experimental errors of 'compass movement due to current flow change' and experimental errors 'serial connection of bulbs'. The long-standing difficulties in science-PCK were 'understanding and response to context' and 'understanding and response to aims mentioned in standard document' and these are not related to physical units but to others. In particular, there are request class materials, activity ideas at the end of the semester and understanding the national curriculum guidelines. These teachers' difficulties should be reflected in the science teaching support system like a teacher's guide compilation, teacher's training curriculum development, etc.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.6
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• pp.1-8
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• 2005

In this paper, we propose a two-stage head tracking algorithm adequate for real-time active camera system having pan-tilt-zoom functions. In the color convergence stage, we first assume that the shape of a head is an ellipse and its model color histogram is acquired in advance. Then, the min-shift method is applied to roughly estimate a target position by examining the histogram similarity of the model and a candidate ellipse. To reflect the temporal change of object color and enhance the reliability of mean-shift based tracking, the target histogram obtained in the previous frame is considered to update the model histogram. In the updating process, to alleviate error-accumulation due to outliers in the target ellipse of the previous frame, the target histogram in the previous frame is obtained within an ellipse adaptively shrunken on the basis of the model histogram. In addition, to enhance tracking reliability further, we set the initial position closer to the true position by compensating the global motion, which is rapidly estimated on the basis of two 1-D projection datasets. In the subsequent stage, we refine the position and size of the ellipse obtained in the first stage by using shape information. Here, we define a robust shape-similarity function based on the gradient direction. Extensive experimental results proved that the proposed algorithm performs head hacking well, even when a person moves fast, the head size changes drastically, or the background has many clusters and distracting colors. Also, the propose algorithm can perform tracking with the processing speed of about 30 fps on a standard PC.