• Journal of Elementary Mathematics Education in Korea
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• v.17 no.3
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• pp.483-501
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• 2013

The present study is to focus on thinking about the possibility of using mathematical modeling in the elementary schools. As well-known, mathematical education in Korea, even though students' high achievement in mathematics, has a lot of problems regarding their attitudes toward mathematics. Mathematical modeling is regarded as playing an important role in helping improve the current problems embedded in elementary mathematics education. Thus, this study reviewed the background that mathematical modeling attracted lots of attentions by many mathematics researchers, the definitions of mathematical modeling and the similarities and differences between problem solving and mathematical modeling. In addition, the processes and main features of well-known three representative models of mathematical modeling were reviewed, and each case of research on mathematical modeling in the elementary schools in Korea and foreign countries was introduced, respectively. Finally, this study suggests that mathematical modeling needs to be dealt with in the elementary school curriculum, together with the improvement of teachers' recognition for mathematical modeling.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.264-265
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• 2008

기존 영상감시 시스템의 물체 탐지 알고리즘은 주로 배경 모델링 기법을 기반으로 하고 있다. 이 기법은 차영상 기법보다는 성능이 뛰어나기는 하지만 여전히 정지 카메라에서만 활용이 가능하고, 주변 환경에 따라 알고리즘 상의 많은 임계값을 현재 상황에 맞춰 일일이 조절해 주어야 한다는 한계점이 있다. 따라서 이 논문에서는 배경모델링 기법을 사용하지 않고 입력되는 영상의 Color 정보를 이용하여 영상 내에 있는 여러 대상을 직접 판단하여 관심 있는 물체를 탐지하는 방법을 제안하고자 한다. 제안된 알고리즘은 먼저 현재의 영상을 하나의 물체로 추정되는 영역이 하나의 영역으로 구분되어지게 간단하게 분할해낸다 그리고 나누어진 영역마다 대표 Color 값을 계산하여 미리 학습된 데이터를 기준으로 Support Vector Domain Description (SVDD) 알고리즘을 사용하여 구별해내고 그 결과를 바탕으로 영역이 무엇인지를 판별해낸다. 이 방법은 정지되어 있는 카메라뿐만 아니라 움직이는 카메라 상에서도 사용되어질 수 있으며 알고리즘 상에서 사용되는 임계값의 종류가 적기 때문에 많은 상황에서 일반적으로 쓰일 수 있다.

• Journal of the Korean Geotechnical Society
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• v.22 no.10
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• pp.5-20
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• 2006

This paper concerns the finite element (FE) modeling approach for NATM tunneling in water bearing ground within the framework of stress-pore pressure coupled analysis. Fundamental interaction mechanism of ground and groundwater lowering was first examined and a number of influencing factors on the results of coupled FE analysis were identified. A parametric study was then conducted on the influencing factors such as soil-water characteristics, location of hydraulic boundary conditions, the way of modeling drainage flow, among others. The results indicate that the soil-water characteristics play the most important role in the tunneling-induced settlement characteristics. Based on the results, modeling guidelines were suggested for stress-pore pressure coupled finite element modeling of NATM tunneling.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10b
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• pp.742-744
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• 2004

본 논문은 복잡한 배경에서의 얼굴 검출에 있어서 다중 특징 추출 데이터로 학습한 계단식 분류기에 의한 방법을 제안한다 얼굴 검출에서 얼굴의 패턴은 상당히 다양한 영상 표현으로 나타나기 때문에 하나의 특징 추출 방법은 사람의 얼굴을 모델링 하기에는 부족하다. 따라서 여기서는 얼굴의 전체적인 지역적인 특징을 나타내는 Subregion과, 얼굴의 주파수 특성에 따라 좀 더 세밀하고 다양한 속성들을 나타내는 Haar 웨이블릿 변환을 이용하여 다중으로 특징을 추출하여 효과적인 모델링을 시도하였다. 특징을 추출한 얼굴과 비얼굴의 패턴(pattern)을 구분하기 위해서 패턴들의 통계적인 특성을 이용하여 각 추출방법에 맞게 학습된 Bayesian 분류기를 직렬로 연결하여 사용하였으며 비얼굴은 얼굴과 유사한 비얼굴(face-like nonface) 패턴들을 사용하여 모델링 하였다. 제안한 얼굴 검출 방식의 성능은 MIT-CMU 시험 영상들을 이용하여 평가하였다. 그 결과 한 가지 특징 추출을 사용하는 것 보다 두 가지 특징 추출을 병행한 계단식 구성이 더 정확한 검출 결과를 나타내었다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.2
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• pp.344-352
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• 2003

An effective algorithm for implementation of which detects moving object from image sequences. predicts the direction of it. and drives the camera in real time is proposed. In static camera, for robust motion detection from a dynamic background scene, the proposed algorithm performs statistical modeling of moving objects and background, and trains the statistical modeling of moving objects and background, and trains the statistical feature of background with the initial parts of sequence which have no moving objects. Active camera moving objects are segmented by following procedure, an improved order adaptive lattice structured linear predictor is used. The proposed algorithm shows robust object tracking results in the environment of static or active camera. It can be used for the unmanned surveillance system, traffic monitoring system, and autonomous vehicle.

• Journal of Broadcast Engineering
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• v.16 no.1
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• pp.178-181
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• 2011

With the development of mobile devices and intelligent surveillance system loaded with pan/tilt cameras, object tracking with non-stationary cameras has become a topic with increasing importancy. Since it is difficult to model a background image in a non-stationary camera environment, colors and texture are the most important features in the tracking algorithm. However, colors in the background similar to those in the target arise instability in the tracking. Recently, we proposed a robust color based tracking algorithm that uses an area weighted centroid shift. In this letter, we update the model such that it becomes more stable against background colors. The proposed algorithm also incorporates time filtering by adding an additional energy term to the energy functional.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.1
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• pp.90-94
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• 2010

In this paper, we propose a vehicle tracking method that can be applied in the intelligent traffic information system. The proposed method mainly consists of two steps: overlap removal and background updating. In order to remove overlap, we detect the overlap based on the location of the vehicle from successive images. Background updating is to calculate a background using statistical analysis of successive images. We collected a set of test images from the traffic monitoring system and experimented. The experimental results show more than 96% of tracking accuracy.

• Journal of KIISE:Software and Applications
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• v.28 no.7
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• pp.501-510
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• 2001

Generally, it is essential to estimate exact disparity for the 3D modeling from stereo images. Because existing methods calculate disparities from a whole image, they require too much cimputational time and bring about the mismatching problem. In this article, using the characteristic that the disparity vectors in stereo images are distributed not equally in a whole image but only exist about the background and obhect, we do a wavelet transformation on stereo images and estimate coarse disparity fields from the reduced lowpass field using area-based method at first-step. From these coarse disparity vectors, we generate disparity histogram and then separate object from background area using it. Afterwards, we restore only object area to the original image and estimate dense and accurate disparity by our two-step pixel-based method which does not use pixel brightness but use second gradient. We also extract feature points from the separated object area and estimate depth information by applying disparity vectors and camera parameters. Finally, we generate 3D model using both feature points and their z coordinates. By using our proposed, we can considerably reduce the computation time and estimate the precise disparity through the additional pixel-based method using LOG filter. Furthermore, our proposed foreground/background method can solve the mismatching problem of existing Delaunay triangulation and generate accurate 3D model.

• Journal of KIISE:Software and Applications
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• v.26 no.12
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• pp.1482-1496
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• 1999

기존의 스테레오 정합 알고리즘은 크게 명암기반기법과 특징기반기법의 두 가지로 나눌 수 있다. 그리고, 각 기법은 그들 나름대로의 장단점을 갖는다. 본 논문은 이 두 기법을 결합하는 새로운 알고리즘을 제안한다. 본 논문에서는 물체모델링을 목적으로 하기 때문에 배경을 제거하여 정합하는 방법을 사용한다. 이를 위해, 정합요소들과 정합유사함수가 정의되고, 정합유사함수는 두 기법사이의 장단점을 하나의 인수에 의해 조절한다. 그 외에도 거리차 지도의 오류를 제거하는 coarse-to-fine기법, 폐색문제를 해결하는 다중윈도우 기법을 사용하였고, 물체의 표면형태를 알아내기 위해 morphological closing 연산자를 이용하여 물체와 배경을 분리하는 방법을 제안하였다. 이러한 기법들을 기반으로 하여 여러가지 영상에 대해 실험을 수행하였으며, 그 결과들은 본 논문이 제안하는 기법의 효율성을 보여준다. 정합의 결과로 만들어지는 거리차 지도는 3차원 모델링을 통해 가상공간상에서 보여지도록 하였다.Abstract Classical stereo matching algorithms can be classified into two major areas; intensity-based and feature-based stereo matching. Each technique has advantages and disadvantages. This paper proposes a new algorithm which merges two main matching techniques. Since the goal of our stereo algorithm is in object modeling, we use images for which background is removed. Primitives and a similarity function are defined. The matching similarity function selectively controls the advantages and disadvantages of intensity-based and feature-based matching by a parameter.As an additional matching strategy, a coarse-to-fine method is used to remove a errorneous data on the disparity map. To handle occlusions, multiple windowing method is used. For finding the surface shape of an object, we propose a method that separates an object and the background by a morphological closing operator. All processes have been implemented and tested with various image pairs. The matching results showed the effectiveness of our method. From the disparity map computed by the matching process, 3D modeling is possible. 3D modeling is manipulated by VRML(Virtual Reality Manipulation Language). The results are summarized in a virtual reality space.

• Journal of Digital Convergence
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• v.15 no.7
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• pp.393-400
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• 2017

Generally, in special effect video and 3D animation design process, character and background's 3D model is built by 3D program like MAYA or 3DS MAX. But in that manual modeling mode, model design needs much time and costs much money. In this paper, two experimental groups are set to prove use 2D photo scan modeling mode to build 3D model is effective and advanced. The first experimental group is modeling the same object by different experimental setting. The second experimental group is modeling the same background by different experimental setting. Through those two experimental groups, we try to find an effective design method and matters need attention when we use photo scan design mode. We aim to get the model from whole experiment and prove photo scan modeling mode is effective and advanced.