• 대한전자공학회논문지SP
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• 제37권5호
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• pp.31-41
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• 2000

본 논문은 입력 영상에 따라 적응적으로 구해진 임계 값을 이용하여 움직임을 검출하는 블럭 단위 움직임 검출 기법을 제안한다 우선, 현재 영상을 블럭의 크기에 따라 블럭화 한 후 각 블럭의 특정 값을 구하고 이 전 영상에서 저장된 블럭 특정 값과의 차이 값을 구한 다음 임계 값을 이용하여 움직임을 검출한다. 본 논문 에서는 적응적인 임계 값을 구하기 위해서 움직임 벡터를 이용하여 움직임 블럭과 배경 블럭을 구분하고 각 각의 영역에 대한 통계척인 분포를 해석하여 움직임 판별을 위한 각 특정 값의 임계 값을 입력 영상에 따라 자동 조정한다 모의 실험을 통하여 블럭의 크기가 움직임 검출 성능에 미치는 영향, 노이즈의 영향, 특정 값의 종류에 따른 검출의 정확도 기존의 움직임 검출 알고리즘과의 성능을 비교 분석한다

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2003년도 추계종합학술대회
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• pp.580-583
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• 2003

본 논문에서는 반복적인 움직임의 있는 경우, 강건하게 해결 할 수 있는 움직임 검출 알고리즘을 제시한다. 기존에 차 영상을 이용한 움직임 검출방법은 밝기나 잡음에는 어느 정도 강건하지만, 일정 영역에서 동작하는 물체의 반복적인 움직임에 대해서는 움직임으로 오 인식하는 문제점을 자주 발생시킨다. 이러한 문제점을 해결하기 위해 영상에서 반복적인 움직임은 특정 영역 상에서만 움직임의 발생된다는 특징을 이용해, 움직임의 가장 많이 발생한 영역을 움직임 영역으로 설정하고, 블록 정합(Block Matching) 시켜 계산된 평균절대오차(MAE)값을 가지고 문제를 해결하는 방법을 제시한다. 실험 결과 제안된 알고리즘은 다양한 반복적인 움직임에 대해 기존의 방법들에 비해 좋은 결과를 얻을 수 있었다.

• 제어로봇시스템학회논문지
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• 제19권1호
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• pp.65-71
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• 2013

In this work, new smart phone based moving target detection is proposed. In order to implement the task, methods of real time image transmission from network camera, motion detecting algorithm and its effective implementation are also addressed. The network camera transfers image data by MJPEG format which contains various information such as data and IP address, and the smart phone separates the image data received through a WiFi module. Later, the image data is converted to a Bitmap image format, and with the help of the embedded OpenCV library on a smart phone and algorithm, it was found that the moving object was identified effectively in terms of real time monitoring and detection.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1199-1201
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• 2005

In the synthetic aperture radar (SAR) system, the motion error is the main phase error sources and the motion compensation is very important. The phase gradient autofocus (PGA) is a state of art technique for phase error correction of SAR. It exploits the redundancy of the phase-error information among range bins by selecting the strongest scatter for each range bin and synthesizes them. The motivation of this paper is based on the observation that the redundancy of phase error is also among the cross-range direction. Moreover, the proposed method applies the weighting function to better utilize the phase error information. The validity of the proposed scheme for PGA is tested with some numerical simulation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권8호
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• pp.3151-3168
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• 2015

Automatic detection of estrus in cows is important in cattle management. This paper proposes a method of estrus detection by automatically checking cattle mounting. We use a side-view video camera and apply computer vision techniques to detect mounting behavior. In particular, we extract motion information to select a potential mount-up and mount-down motion and then verify the true mounting behavior by considering the direction, magnitude, and history of the mount motion. From experimental results using video data obtained from a Korean native cattle farm, we believe that the proposed method based on the abrupt change of a mounting cow's height and motion history information can be utilized for detecting mounting behavior automatically, even in the case of fence occlusion.

• 한국정보전자통신기술학회논문지
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• 제12권1호
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• pp.22-28
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• 2019

This paper presents a method for detection of an emergency signal expressed by arm gestures based on motion segmentation and face area detection in the surveillance system. The important indicators of emergency can be arm gestures and voice. We define an emergency signal as the 'Help Me' arm gestures in a rectangle around the face. The 'Help Me' arm gestures are detected by tracking changes in the direction of the horizontal motion vectors of left and right arms. The experimental results show that the proposed method successfully detects 'Help Me' emergency signal for a single person and distinguishes it from other similar arm gestures such as hand waving for 'Bye' and stretching. The proposed method can be used effectively in situations where people can't speak, and there is a language or voice disability.

• International Journal of Computer Science & Network Security
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• 제21권4호
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• pp.131-139
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• 2021

In current time, anomaly detection is the primary concern of the administrative authorities. Suspicious activity identification is shifting from a human operator to a machine-assisted monitoring in order to assist the human operator and react to an unexpected incident quickly. These automatic surveillance systems face many challenges due to the intrinsic complex characteristics of video sequences and foreground human motion patterns. In this paper, we propose a novel approach to detect anomalous human activity using a hybrid approach of statistical model and Genetic Programming. The feature-set of local motion patterns is generated by a statistical model from the video data in an unsupervised way. This features set is inserted to an enhanced Genetic Programming based classifier to classify normal and abnormal patterns. The experiments are performed using publicly available benchmark datasets under different real-life scenarios. Results show that the proposed methodology is capable to detect and locate the anomalous activity in the real time. The accuracy of the proposed scheme exceeds those of the existing state of the art in term of anomalous activity detection.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 하계종합학술대회 논문집(4)
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• pp.206-209
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• 2000

Almost vision application systems use 2-D information by taking only one camera. Recently it arises to utilize 3-D information, which is distance from camera to object, because 2-D information is not sufficient. Therefore, we take stereo camera system. In motion detection algorithm using stereo vision, it operates like one camera system, which takes advantage of correlation, edge, and difference algorithm, when it detects any motion. At that time, to detect motion, it compares two images, which is from two cameras, to calculate disparity that contains distance information. By disparity, it can compute real distance and size of object information. We describe a motion detection algorithm which computes 3-D distance and object size in real time.

• Journal of Information Technology Applications and Management
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• 제10권3호
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• pp.45-54
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• 2003

Security system with web camera remarkably has been developed at an Internet era. Using transmitted images from remote camera, the system can recognize current situation and take a proper action through web. Existing motion detection methods use simply difference image, background image techniques or block matching algorithm which establish initial block by set search area and find similar block. But these methods are difficult to detect exact motion because of useless noise. In this paper, the proposed method is updating changed background image as much as $N{\times}M$pixel mask as time goes on after get a difference between imput image and first background image. And checking image pixel can efficiently detect motion by computing fixed distance pixel instead of operate all pixel.

• 방송공학회논문지
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• 제18권2호
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• pp.167-177
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• 2013

이 논문에서는 향상된 움직임 적응적 디인터레이싱 알고리듬을 제안한다. 정확한 움직임 정보탐색을 위하여 세 가지 부분으로 구성된다 : (1) Modified Edge-based Line Average(MELA) 기법, (2) 연속된 5개의 필드에서의 움직임 탐색, 그리고 (3) 블록기반의 지역적 특성을 포함한다. 움직임 검출부분에서는 FIR 필터를 이용한다. 이것은 물체의 움직임의 내부를 정확하게 탐색 할 뿐만 아니라, 영상에 포함된 잡음도 줄일 수 있는 향상된 기법을 이용함으로써 계산 할 수 있다. 검출된 움직임의 정도에 따라서 가중치를 구하여 공간적 기법과 시간적 기법을 결합시킨다. 제안된 방법의 영상 시퀀스에 대한 실험 결과는 기존의 방법들에 비하여 주관적, 객관적인 비교에서 우수함을 보여준다.