• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅳ
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• pp.1944-1947
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• 2003

In this paper, we propose a dynamic-based compression system by creating mosaic background and transmitting the change information. A dynamic mosaic of the background is progressively integrated in a single image using the camera motion information. For the camera motion estimation, we calculate affine motion parameters for each frame sequentially with respect to its previous frame. The camera motion is robustly estimated on the background by discriminating between background and foreground regions. The modified block-based motion estimation is used to separate the back-ground region.

• 한국멀티미디어학회논문지
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• 제18권2호
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• pp.268-276
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• 2015

This article analyzes the background representation of 3D animation and look at what its proper background expression. With the development of computer graphics technology, the background of the 3D animations can be expressed as The actual background. In contrast, "The Smurfs" which was released recently was created to take the actual background. However, 3D animation with real background is not appropriate in terms of creative expression space in the main role of the animation. In this Study, we analyze the character and background of the animation made in 3D graphics. Based on this, we propose a correct representation of 3D animation background.

• 한국정보전자통신기술학회논문지
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• 제6권2호
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• pp.81-87
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• 2013

Motion segmentation is a fundamental technique for analysing image sequences of real scenes. A process of identifying moving objects from data is a typical task in many computer vision applications. In this paper, we propose motion segmentation that generally consists from background subtraction and foreground pixel segmentation. The Approximated Median Filter (AMF) was chosen to perform background modeling. Motion segmentation in this paper covers RGB video data.

• 한국정보전자통신기술학회논문지
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• 제7권1호
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• pp.61-67
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• 2014

Motion segmentation is a fundamental technique for analysing image sequences of real scenes. A process of identifying moving objects from data is a typical task in many computer vision applications. In this paper, we propose motion segmentation that generally consists from background subtraction and foreground pixel segmentation. The Approximated Median Filter(AMF) was chosen to perform background modeling. Motion segmentation in this paper covers RGB video data.

• 대한수학교육학회지:학교수학
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• 제8권2호
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• pp.239-263
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• 2006

교육의 결과인 학업성취도에 영향을 미치는 변인이 무엇이며, 이러한 변인들이 어느 정도의 교육적 효과를 나타내는지 탐색하는 것은 매우 중요한 연구과제이다. 본 연구는 국가수준 학업성취도 평가의 중요한 축을 이루는 배경변인 연구의 전반적인 특정을 탐색하고, 2004년 학업성취도 평가에서 나타난 배경변인과 수학 학업 성취도 사이의 관계를 분석하였다. 학생 및 학교 배경변인과 수학 학업성취도 사이의 관계 분석에서 나타난 특징을 살펴보고, 그러한 특정을 바탕으로 교육정책적 제언을 하였다.

• Journal of Information Processing Systems
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• 제15권5호
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• pp.1218-1230
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• 2019

This study proposes a novel video traffic flow detection method based on machine vision technology. The three-frame difference method, which is one kind of a motion evaluation method, is used to establish initial background image, and then a statistical scoring strategy is chosen to update background image in real time. Finally, the background difference method is used for detecting the moving objects. Meanwhile, a simple but effective shadow elimination method is introduced to improve the accuracy of the detection for moving objects. Furthermore, the study also proposes a vehicle matching and tracking strategy by combining characteristics, such as vehicle's location information, color information and fractal dimension information. Experimental results show that this detection method could quickly and effectively detect various traffic flow parameters, laying a solid foundation for enhancing the degree of automation for traffic management.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권4호
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• pp.782-804
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• 2011

In video-based recognition systems, stationary cameras are used to monitor an area of interest. These systems focus on a segmentation of the foreground in the video stream and the recognition of the events occurring in that area. The usual approach to discriminating the foreground from the video sequence is background subtraction. This paper presents a novel background subtraction method based on a probabilistic approach. We represent the posterior probability of the foreground based on the current image and all past images and derive an updated method. Furthermore, we present an efficient fusion method for the color and edge information in order to overcome the difficulties of existing background subtraction methods that use only color information. The suggested method is applied to synthetic data and real video streams, and its robust performance is demonstrated through experimentation.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2003년도 추계종합학술대회
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• pp.741-744
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• 2003

본 논문은 모자이크 배경을 생성하고 변화되는 정보만을 전송함으로서 동적기반 압축시스템을 제안한다. 동적 모자이크 배경은 카메라 움직임 정보를 이용하여 단일영상으로 점진적으로 통합된다. 카메라 움직임 예측을 위해 각각의 영상들과 이전영상과의 원근투영 매개변수를 순차적으로 계산하였다. 카메라 움직임은 배경영역과 전경영역에서 식별함으로서 배경상에서 강건하게 계측된다. 수정된 블록기반 움직임계측은 배경영역을 분리하는데 이용되었다.

• Journal of Information Processing Systems
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• 제15권2호
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• pp.344-358
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• 2019

Surveillance cameras have installed in many places because security and safety is becoming important in modern society. Through surveillance cameras installed, we can deal with troubles and prevent accidents. However, watching surveillance videos and judging the accidental situations is very labor-intensive. So now, the need for research to analyze surveillance videos is growing. This study proposes an algorithm to track multiple persons using SURF and background subtraction. While the SURF algorithm, as a person-tracking algorithm, is robust to scaling, rotating and different viewpoints, SURF makes tracking errors with sudden changes in videos. To resolve such tracking errors, we combined SURF with a background subtraction algorithm and showed that the proposed approach increased the tracking accuracy. In addition, the background subtraction algorithm can detect persons in videos, and SURF can initialize tracking targets with these detected persons, and thus the proposed algorithm can automatically detect the enter/exit of persons.

• 전자공학회논문지
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• 제50권8호
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• pp.238-244
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• 2013

에너지 분산형 X-선 형광(EDXRF) 분석에서 X-선 스펙트럼에 존재하는 컨티넘(continuum)의 추정 및 제거는 필수적이다. 이를 위해 일반적으로 사용되는 알고리즘들은 많은 주의가 필요하며 복잡하다. 보통 이 알고리즘들은 제약적이거나 컨티넘의 데이터나 모양에 대한 가설을 필요로 한다. 본 논문에서는 제안된 에너지 분산형 X-선 형광 스펙트럼을 위한 효율적인 배경(background) 보정 방법은 배경 모델링과 배경 보정으로 구성된다. 이 방법은 스펙트럼에서 백그라운드영역과 피크영역을 구분하는 기본 개념을 기반으로 하며 성능향상을 위하여 SNIP알고리즘을 사용한다. 스펙트럼으로부터 배경에 속하는 점들을 획득한 후 이를 기반으로 곡선 근사화를 통해 배경을 모델링한다. 이후 획득된 배경 모델을 원 스펙트럼에서 뺌으로써 배경이 보정된 스펙트럼을 얻는다. 제안된 방법은 상대적으로 적은 사전 지식을 요구하면서 기존의 몇몇 방법들에 비해 우수한 결과를 보여주었다.