• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.12
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• pp.1537-1543
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• 1999

In this paper, PSD(Position Sensitive Detector) sensor system that estimates position for moving objects in 2D plane is developed. PSD sensor is used to measure the position of an incidence light in real-time. To get the position of light source of moving target, a new parameter calibration algorithm and neural network technique are proposed and applied. Real-time position measurements of the mobile robot with light source is examined to validate the proposed method. It is shown that the proposed technique provides accurate position estimation of the moving object.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2006.04a
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• pp.177-180
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• 2006

In this paper we proposed a method of automatic point segmentation acquired by 2D laser scanner to recognize moving objects. Recently, Laser scanner is noticed as a new method in the field of close range 3D modeling. But the majority of the researches are pointed on precise 3D modeling of static objects using expensive 3D laser scanner. 2D laser scanner is relatively cheap and can obtain 2D coordinate information of moving object's surface or can be utilized as 3D laser scanner by rotating the system body. In these reasons, some researches are in progress, which are adopting 2D laser scanner to robot control systems or detection of objects moving along linear trajectory. In our study, we automatically segmented point data of 2D laser scanner thus we could recognize each of the object passing through a section.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10c
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• pp.83-87
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• 2006

Similarity search in moving object trajectories is an active area of research. In this paper, we introduce a new concept of measure that computes spatial distance (similarity) between two trajectories of moving objects on road networks. In addition, we propose an algorithm that generates a sequence of matching edge pairs for two trajectories that ate to be compared and computes spatial distance between them which is non Euclidian in nature. With an example, we explain how our algorithm works to show spatial similarity between trajectories of moving objects in spatial network.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1387-1389
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• 1987

In this paper, we describe not only extraction method of moving object by difference image but also automatic target tracking algorithm. Proposed algorithm track the moving target by the calculation of moving target's center. The results show that this algorithm can apply to practical device such as real time target tracker.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.96.6-96
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• 2002

In this study an image processing system is designed and developed, which can detect and assort some defects on the surface of an object moving with high speed. For real time surface detection of high speed moving object, the fast processing should be managed and the image information including some surface features should be captured. It is difficult to acquire the noise free image due to various light sources and high speed moving materials under the environment of the general industrial site. In general, because pre-processing methods are employed for getting a noise free feature, the image processing speed has some limitation and the expensive image processing devices are required. This...

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.425-428
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• 2003

Recently, the IDS(Intrusion Detection System) using a video camera is an important part of the home security systems which start gaining popularity. However, the video intruder detection has not been widely used in the home surveillance systems due to its unreliable performance in the environment with abrupt illumination change. In this paper, we propose an effective moving edge extraction algorithm from a sequence image. The proposed algorithm extracts edge segments from current image and eliminates the background edge segments by matching them with reference edge list, which is updated at every frame, to find the moving edge segments. The test results show that it can detect the contour of moving object in the noisy environment with abrupt illumination change.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.10 no.1
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• pp.36-42
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• 2001

In this paper, PSD(Position Sensitive Detector) sensor system that estimates position for moving objects in 2D plane is developed. PSD sensor is used to measure the position the position of and incidence light in real-time. To get the position of light source of moving target, a new parameter calibration algorithm and neural network technique are proposed and applied. Real-time position measurements of the mobile robot with light source is examined to validate the proposed method. It is shown that the proposed technique provides accurate position estimation of the moving object.

• Journal of The Korean Association For Science Education
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• v.17 no.4
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• pp.373-381
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• 1997

To investigate the preconceptions on the reference frame and relativity of motion, 251 of grade 7 pupils were selected. The questionnaire has 15 questions consisted of four test domains made by the researchers: object looks rest or moving in the rest frame, object looks rest or moving in the moving frame. The result shows that pupils took the observations in the moving frame for those in the rest frame, or vice versa. In addition, their answers varied according as the context of the observation differed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.8C
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• pp.1175-1183
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• 2004

This paper propose a method to trace a moving object based on the information directly obtained from MPEG-2 compressed video stream without decoding process. In the proposed method, the motion flow is constructed from the motion vectors involved in compressed video and then we calculate the amount of pan, tilt, zoom associated with camera operations using generalized Hough transform. The local object motion can be extracted from the motion flow after the compensation with the parameters related to the global camera motion. The moving object is designated initially by a user via bounding box. After then automatic tracking is performed based on the mean-shift algorithm of the motion flows of the object. The proposed method can improve the computation speed because the information is directly obtained from the MPEG-2 compressed video, but the object boundary is limited by blocks rather than pixels.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.5
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• pp.39-50
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• 2017

Moving object tracking techniques can be considered as one of the most essential technique in the video understanding of which the importance is much more emphasized recently. However, irregularity of light condition in the video, variations in shape and size of object, camera motion, and occlusion make it difficult to tracking moving object in the video. Swarm based methods are developed to improve the performance of Kalman filter and particle filter which are known as the most representative conventional methods, but these methods also need to consider dynamic property of moving object. This paper proposes adaptive parameter control method which can dynamically change weight value among parameters in particle swarm optimization. The proposed method classifies each particle to 3 groups, and assigns different weight values to improve object tracking performance. Experimental results show that our scheme shows considerable improvement of performance in tracking objects which have nonlinear movements such as occlusion or unexpected movement.