• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.6
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• pp.1304-1311
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• 2003

Target tracking in a real world situation is difficult problem because of continuous variations in images, huge amounts of data, and high processing speed demands. The problem becomes even harder in the case of sea background. This paper presents an initial study of neural network based method for target detection and tracking in cluttering environment. The approach uses a combination of differential motion analysis, Kohonen self-organizing network and region growing method. The network is capable of detecting the mass-centers of moving objects within one frame. The history of neurons positions in the sequential frames approximates the traces of the targets. The experiments done with the network in simulated environment showed promising results.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.6
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• pp.137-142
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• 2020

As research on security systems using IoT (Internet of Things) devices increases, the need for research to track the location of specific objects is increasing. The goal is to detect the movement of objects in real-time and to predict the radius of movement in short time. Many studies have been done to clearly recognize and detect moving objects. However, it does not require the sharing of information between cameras that recognize objects. In this paper, using the device information of the camera and the video information taken from the camera, the movement radius of the object is predicted and information is shared about the camera within the radius to provide the movement path of the object.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.7
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• pp.650-657
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• 2012

An effective dual-mode camera system(a passive wide-angle camera and a pan-tilt-zoom camera) is proposed in order to improve the performance of visual surveillance. The fixed wide-angle camera is used to monitor large open areas, but the moving objects on the images are too small to view in detail. And, the PTZ camera is capable of increasing the monitoring area and enhancing the image quality by tracking and zooming in on a specific moving target. However, its FOV (Field of View) is limited when zooming in on a specific target. Therefore, the cooperation of wide-angle and PTZ cameras is complementary. In this paper, we propose an automatic initial set-up algorithm and coordinate transform method from the wide-angle camera coordinate to the PTZ one, which are necessary to achieve the cooperation. The automatic initial set-up algorithm is able to synchronize the views of two cameras. When a moving object appears on the image plane of a wide-angle camera after the initial set-up positioning, the obtained values of the wide-angle camera should be transformed to the PTZ values based on the coordinate transform method. We also develope the PTZ control method. Various in-door and out-door experiments show that the proposed dual-camera system is feasible for the effective visual surveillance.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.5 no.1
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• pp.1-6
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• 2012

In this paper, we propose a HMM(Hidden Markov Model)-based segmentation method to model shadows as well as foreground and background regions. The shadow of moving objects often keeps from visual tracking. We propose an HMM-based segmentation method which classifies each object in real time. In the case of traffic monitoring movies, the effectiveness of the proposed method was proved by experiments.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.3
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• pp.349-354
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• 2007

To generate the template of a detected object and to track the overlapped object and the object covered by other objects correctly are important research problems in visual surveillance. The frame difference is not capable of generating the template of slowly moving object. To get around the drawback of the conventional frame difference, we propose a new algorithm for generating a template using adaptive 3-frame difference.

• ETRI Journal
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• v.43 no.4
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• pp.617-629
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• 2021

Although the actual visual simultaneous localization and mapping (SLAM) algorithms provide highly accurate tracking and mapping, most algorithms are too heavy to run live on embedded devices. In addition, the maps they produce are often unsuitable for path planning. To mitigate these issues, we propose a completely closed-loop online dense RGB-D SLAM algorithm targeting autonomous indoor mobile robot navigation tasks. The proposed algorithm runs live on an NVIDIA Jetson board embedded on a two-wheel differential-drive robot. It exhibits lightweight three-dimensional mapping, room-scale consistency, accurate pose tracking, and robustness to moving objects. Further, we introduce a navigation strategy based on the proposed algorithm. Experimental results demonstrate the robustness of the proposed SLAM algorithm, its computational efficiency, and its benefits for on-the-fly navigation while mapping.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.868-871
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• 2009

We propose an global color model based method for tracking motions of multiple human using a networked multiple-camera system in intelligent space as a human-robot coexistent system. An intelligent space is a space where many intelligent devices, such as computers and sensors(color CCD cameras for example), are distributed. Human beings can be a part of intelligent space as well. One of the main goals of intelligent space is to assist humans and to do different services for them. In order to be capable of doing that, intelligent space must be able to do different human related tasks. One of them is to identify and track multiple objects seamlessly.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.623-628
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• 2008

We present a new method of extracting foreground object from background image for vision-based game interface. Background Subtraction is an important preprocessing step for extracting the features of tracking objects. The image is divided into the cells where the Local Histogram with Gaussian kernel is computed and compared with the corresponding one using Bhattacharyya distance measure. The histogram-based method is partially robust against illumination change, noise and small moving objects in background. We propose a Multi-Scaled Integral Histogram approach for noise suppression and fast computation.

• Proceedings of the KOSOMBE Conference
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• v.1994 no.05
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• pp.32-34
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• 1994

An automatic multiframe procedure for tracking signalized points on multiple, differently moving discontinuous surface is described. The position of markers which attached on human body give us some important information such as velocity, acceleration, angular velocity and angular acceleration, etc, of the rigid objects. Generally, the detected objects occufying some area in images rather than a point because of the generic size of the marks or the smeared effects of the camera. To solve the problem we used a modified clustering algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.587-590
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• 2004

In this paper proposed a HMM(Hidden Martov Model)-based segmentation method which is able to model shadows as well as foreground and background regions. Shadow of moving objects often obstruct visual tracking. We propose an HMM-based segmentation method which classifies in real time oath objects. In the case of traffic monitoring movies, the effectiveness of the proposed method has been proven through experimental results