• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.5C
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• pp.505-513
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• 2009

This paper proposes a real-time foreground segmentation and background substitution method for protecting the privacy on visual communication. Previous works on this topic have some problems with the color and shape of foreground and the capture device such as stereo camera. we provide a solution which can segment the foreground in real-time using fixed mono camera. For improving the performance of a foreground extraction, we propose the Temporal Foreground Probability Model (TFPM) by modeling temporal information of a video. Also we provide an boundary processing method for natural and smooth synthesizing that using alpha matte and simple post-processing method.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.750-754
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• 2007

본 논문은 실내의 로비나 복도에 설치된 방범 카메라로부터 얻어진 일련의 영상으로부터 '걷기', '뛰기', '앉기', '일어서기', '넘어짐'의 비교적 짧은 시간에 일어나는 인간 행동들을 실시간으로 인식하는 시스템의 구현에 관해 다룬다. 먼저 입력으로 받은 영상을 계층적 색인 구조를 갖는 다중 가우시안 기반의 배경 모델을 이용하여 윤곽을 추출하고 객체를 인식하여 시간차에 의한 가중치로 누적하여 시간 템플릿을 만든다. 만들어진 시간 템플릿으로부터 특징을 추출하여 신경망 모델에 적용하여 5가지 인간행동을 구분한다. 구현된 시스템으로 인간행동 인식 실험을 수행하였는데, 실험 참가자들의 행동 방식이 약간씩 달랐음에도 불구하고 높은 인식률을 보여주었다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.808-810
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• 2011

The background estimation algorithms had a significant impact on the performance of image processing and recognition. In this paper, background estimation algorithms were analysis of complexity and performance as preprocessing of image recognition. It was evaluated the performance of Gaussian Running Average, Mixture of Gaussian, and KDE algorithm. The simulation results show that KDE algorithm outperforms compared to the other algorithms.

• Journal of the Korea Society of Computer and Information
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• v.16 no.4
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• pp.73-81
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• 2011

In this paper, an improved block-based background modeling technique using adaptive parameter estimation that judiciously adjusts the number of model histograms at each frame sequence is proposed. The conventional block-based background modeling method has a fixed number of background model histograms, resulting to false negatives when the image sequence has either rapid illumination changes or swiftly moving objects, and to false positives with motionless objects. In addition, the number of optimal model histogram that changes each type of input image must have found manually. We demonstrate the proposed method is promising through representative performance evaluations including the background modeling in an elevator environment that may have situations with rapid illumination changes, moving objects, and motionless objects.

• The Journal of the Korea Contents Association
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• v.22 no.3
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• pp.179-188
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• 2022

The purpose of this study is to analyze the variables affecting the institutional commitment of college students. Based on the relevant literature review, this study subdivided institutional commitment of college students into three; academic integration, social integration and institutional commitment. To achieve the goals, the hierarchical regression analysis was conducted using KELS(Korea Educational Longitudinal Survey) data collected by KEDI in 2018. Major findings are as follows: factors related to college experiences such as learning styles, negligence of learning, college climate, interaction with faculty members or peer group were found to be associated with the institutional commitment of college students. With regard to students' background, male students revealed lower level of academic integration and institutional commitment. The regression model disclosed that students from medicine demonstrated higher social integration compared to other majors. Based on the findings of the study, policy implications were discussed.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.4
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• pp.733-739
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• 2012

In this paper, a smoke detection algorithm robust to brightness and color variations depending on time and weather is proposed. The proposed smoke detection algorithm specifies the candidate region using difference images of input and background images, determines smoke by comparing feature coefficients of Gaussian mixture model of difference images. Thresholds for specifying candidate region is divided by four levels according to average brightness and chrominance of input images. Clusters of Gaussian mixture models of difference images are aligned according to average brightness. Smoke is determined by comparing distance of Gaussian mixture model parameters. The proposed algorithm is implemented by media dedicated DSP. As results of experiments, it is shown that the proposed algorithm is effective to detect smoke with camera installed outdoor.

• The Journal of Korean Physical Therapy
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• v.14 no.3
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• pp.418-432
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• 2002

본 연구의 목적은 다음과 같이 네 가지이다. 첫째, dual-strategy hypothesis 모델의 이론적인 배경을 서술한다. 둘째, 보행시작 시 (Gait Initiation)와 장애물 보행시작 (Stepping over obstacles)시의 motor task를 dual-strategy hypothesis 모델의 관정에서 서술한다. 셋째, 파킨슨씨 환자군과 뇌졸증 환자군을 이 모델의 관점에서 서술한다. 마지막으로, dual strategy hypothesis모델의 임상적용 가능성에 대해서 간단히 서술하는 것이다.

• Proceedings of the Korea Water Resources Association Conference
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• 1994.02a
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• pp.213-219
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• 1994

• 월간낙농육우
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• v.27 no.10 s.306
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• pp.157-161
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• 2007

• 대학교육
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• s.173
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• pp.34-40
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• 2011