• Journal of Korea Multimedia Society
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• v.6 no.3
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• pp.409-418
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• 2003

Object tracking in video is one of subject that computer vision and several practical application field have interest in several years. This paper proposes real time object tracking and face region extraction method that can be applied to security and supervisory system field. For this, in limited environment that camera is fixed and there is seldom change of background image, proposed method detects position of object and traces motion using difference between input image and background image. The system creates adaptive background image and extracts pixels in object using line scan method for more stable object extraction. The real time object tracking is possible through establishment of MBR(Minimum Bounding Rectangle) using extracted pixels. Also, effectiveness for security and supervisory system is improved due to extract face region in established MBR. And through an experiment, the system shows fast real time object tracking under limited environment.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.1
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• pp.111-121
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• 2011

Intelligent video analysis systems require techniques which can predict accidents and provide alarms to the monitoring personnel. In this paper, we present an abnormal behavior analysis technique based on adaptive background generation. More specifically, abnormal behaviors include fence climbing, abandoned objects, fainting persons, and loitering persons. The proposed video analysis system consists of (i) background generation and (ii) abnormal behavior analysis modules. For robust background generation, the proposed system updates static regions by detecting motion changes at each frame. In addition, noise and shadow removal steps are also were added to improve the accuracy of the object detection. The abnormal behavior analysis module extracts object information, such as centroid, silhouette, size, and trajectory. As the result of the behavior analysis function objects' behavior is configured and analyzed based on the a priori specified scenarios, such as fence climbing, abandoning objects, fainting, and loitering. In the experimental results, the proposed system was able to detect the moving object and analyze the abnormal behavior in complex environments.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.3
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• pp.387-391
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• 2008

For the detection of moving objects, background subtraction methods are widely used. In case the background has variation, we need to update the background in real-time for the reliable detection of foreground objects. Gaussian mixture model (GMM) combined with probabilistic learning is one of the most popular methods for the real-time update of the background. However, it does not work well in the complex and dynamic backgrounds with high traffic regions. In this paper, we propose a new method for modelling and updating more reliably the complex and dynamic backgrounds based on the probabilistic learning and the layered processing.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.05a
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• pp.352-355
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• 2000

In this paper, we propose an adaptive thresholding for edge detection. first, we got histograms for background image and image with moving object, respectively. Then we make difference histogram between histograms of background and object image. A thresholding value is decided using gradient of peak to peak in the difference histogram. The experimentation is processed using a moving car in the road. The result is that edge is detected well regardless of the brightness.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.06a
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• pp.284-287
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• 2016

영상에서 배경으로부터 객체를 분류하는 영상 분류 알고리즘은 물체 인식 및 추적 등 다양한 응용분야에서 중요하다. 본 논문에서는 고정된 카메라에서 다수의 초기 프레임을 참조하여 실시간 영상 분류 방법을 제안한다. 먼저 전경과 배경을 구분하는 확률모델을 제안하였으며 초기 프레임 동안에 카메라의 특성을 추출하여 카메라에 적응적으로 영상을 분류한다. 또한 분류된 영상에서 human의 특징을 이용하여 분류된 결과를 보정하는 방법을 제안한다. 마지막으로 제안한 알고리즘의 실시간 분류 처리를 위하여 복잡도를 최소화 하였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.6A
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• pp.610-617
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• 2002

In this paper, a new intermediate view reconstruction technique by using a disparity estimation method based-on the adaptive matching window size is proposed. In the proposed method, once the feature values are extracted from the input stereo image, then the matching window size for the intermediate view reconstruction is adaptively selected in accordance with the magnitude of this feature values. That is, coarse matching is performed in the region having smaller feature values while accurate matching is carried out in the region having larger feature values by comparing with the predetermined threshold value. Accordingly, this new approach is not only able to reduce the mismatching probability of the disparity vector mostly happened in the accurate disparity estimation with a small matching window size, but is also able to reduce the blocking effect occurred in the disparity estimation with a large matching window size. Some experimental results on the 'Parts' and 'Piano' images show that the proposed method improves the PSNR about 2.32∼4.16dB and reduces the execution time to about 39.34∼65.58% than those of the conventional matching methods.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2387-2390
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• 2003

움직이는 물체의 자동 분할은 컴퓨터 비젼의 여러 응용분야에서 중요한 문제로 대두되고 있다. 본 논문에서는 감시 시스템에서 에지와 적응적 임계값을 이용한 효과적인 자동 움직임 분할 방법을 제안하였다. 먼저 연속 영상에서 현재 영상과 배경 영상과의 차를 얻어서 그 히스토그램을 만든다. 이 때 앞에서 얻은 히스토그램은 영상 잡음의 평균이 0 인 가우시안 분포를 가진다고 가정한다. 그리고, 이 히스토그램을 이용하여 영상잡음의 분산을 찾는다 이 분산 값을 이용하여 적응적 임계값과 움직임 영역창을 결정한다. 적응적 임계값에 의한 결과 영상에서 움직이는 물체를 분할하기 위해 본 논문에서는 움직임 영역창을 이용하는 방법을 제안하였다. 이 움직임 영역창에 의해 더욱 효과적인 움직임 분할이 이루어진다. 또, 잡음의 제거를 위해 수학적 모폴로지(mathematical morphology)와 화소의 연결성이 이용된다.

• Korean Journal of Childcare and Education
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• v.8 no.4
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• pp.53-76
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• 2012

The purpose of this study was to find out the effect of background variables, development stage, and perception of accountability on kindergarten teachers' adaptation to the teaching profession. The researchers surveyed 224 teachers in public and private kindergarten. The results of the study are as follows: First, in terms of age, the older they were, the better teachers adjusted to the teaching profession. As for their teaching career, the more teaching experience they had, the better teachers adapted to the teaching profession, but there were no significant differences between 6-10 years and more than 11 years. As to the level of education, four-year college graduates or graduate school graduates adjusted better than two-year college graduates. Second, teachers in the Capability Development Stage and Growth-Enthusiasm Stage showed a higher degree of adaptation than those in the Entrance-Acceptance Stage. Finally, the higher perception of accountability they have, the better teachers could adapt to the teaching profession. Among the categories of accountability, the professional accountability affected most highly the teachers' adaptation to the teaching profession.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.9B
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• pp.1267-1276
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• 2001

본 논문은 스테레오 시차정보를 이용하여 스테레오 비젼 시스템에서 표적물체의 영역 및 위치를 구하고, 표적물체를 제외한 배경을 분리함으로써 표적물체 영역을 효과적으로 추출할 수 있는 새로운 알고리즘을 제시하였다. 즉, 제안한 알고리즘은 스테레오 비젼 시스템에서 얻어지는 양안시차 정보와 각 픽셀의 유사도를 이용하여 1차적으로 배경을 분리한 후 그 결과에 히스토그램을 적용하여 최종적으로 표적물체 영역을 추출하였다. 실험 결과 제안한 알고리즘은 스테레오 입력 영상에서 배경잡음과 관계없이 표적 물체영역을 추출할 수 있었고, 이의 구현으로 스테레오 원격작업 시스템이나 적응적인 스테레오 물체 추적기 등의 구현 가능성을 제시하였다.

• Journal of Advanced Navigation Technology
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• v.10 no.1
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• pp.48-56
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• 2006

This paper proposes an efficient preprocessing technique for a binary centroid tracker in correlated image sequences. It is known that the following factors determine the performance of the binary centroid target tracker: (1) an efficient real-time preprocessing technique, (2) an exact target segmentation from cluttered background images and (3) an intelligent tracking window sizing, and etc. The proposed centroid tracker consists of an adaptive segmentation method based on novel distance features and an efficient real-time preprocessing technique in order to enhance the distinction between the objects of interest and their local background. Various tracking experiments using synthetic images as well as real Forward-Looking InfraRed (FLIR) images are performed to show the usefulness of the proposed methods.