• The Journal of Korea Robotics Society
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• v.2 no.1
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• pp.21-28
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• 2007

The Intelligent Space(ISpace) provides challenging research fields for surveillance, human-computer interfacing, networked camera conferencing, industrial monitoring or service and training applications. ISpace is the space where many intelligent devices, such as computers and sensors, are distributed. According to the cooperation of many intelligent devices, the environment, it is very important that the system knows the location information to offer the useful services. In order to achieve these goals, we present a method for representing, tracking and human following by fusing distributed multiple vision systems in ISpace, with application to pedestrian tracking in a crowd. And the article presents the integration of color distributions into particle filtering. Particle filters provide a robust tracking framework under ambiguity conditions. We propose to track the moving objects by generating hypotheses not in the image plan but on the top-view reconstruction of the scene. Comparative results on real video sequences show the advantage of our method for multi-object tracking. Also, the method is applied to the intelligent environment and its performance is verified by the experiments.

• Journal of the Korea Society of Computer and Information
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• v.23 no.8
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• pp.9-16
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• 2018

In this paper, a kidnapping detection scheme in which human pose estimation is used to classify accurately between kidnapping cases and normal ones is proposed. To estimate human poses from input video, human's 10 joint information is extracted by OpenPose library. In addition to the features which are used in the previous study to represent the size change rates and the regularities of human activities, the human pose estimation features which are computed from the location of detected human's joints are used as the features to distinguish kidnapping situations from the normal accompanying ones. A frame-based kidnapping detection scheme is generated according to the selection of J48 decision tree model from the comparison of several representative classification models. When a video has more frames of kidnapping situation than the threshold ratio after two people meet in the video, the proposed scheme detects and notifies the occurrence of kidnapping event. To check the feasibility of the proposed scheme, the detection accuracy of our newly proposed scheme is compared with that of the previous scheme. According to the experiment results, the proposed scheme could detect kidnapping situations more 4.73% correctly than the previous scheme.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.4
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• pp.461-468
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• 2003

In a sequence of images obtained by surveillance cameras, facial regions appear very small and their colors change abruptly by lighting condition. This paper proposes a new face detection scheme, robust on complex background, small size, and lighting conditions. The proposed method is consisted of three processes. In the first step, the candidates for the face regions are selected using face color distribution and motion information. In the second stage, the non-face regions are removed using face color ratio, boundary ratio, and average of column-wise intensity variation in the candidates. The face regions containing eyes and mouth are segmented and classified, and then they are scored using their topological relations in the last step. To speed up and improve a performance the above process, a block based image segmentation technique is used. The experiments have shown that the proposed algorithm detects faced regions with more than 91% of accuracy and less than 4.3% of false alarm rate.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.3
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• pp.362-367
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• 2010

In this paper, we describe implementation of FPGA-based Nios II embedded processor system and linux device driver for image monitoring system which is supplement weakness for fixed surveillance area of existing CCTV system and by manual operation of the camera's moving. Altera Nios II processor 8.0 is supported MMU which is stable and efficient managed memory. We designed the image monitoring and control system by using Altera Nios II soft-core processor system which is flexible in various application and excellent adaptability. By implementation of camera device driver and VGA decvice driver for Linux-based Nios II system, we implemented image serveillance system for Nios II embedded processor system.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.1550-1555
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• 2011

This paper presents the system interface standard that are associated with additional devices like sensor nodes as well as fire monitoring panel, panic button and emergency call in city railroad environment. Existing fire monitoring panel, panic button and emergency call system is responsible for fire detection and alarm, emergency alarm and communication with the manager. Recently, researches that are associated with NVR-based intelligent integrated surveillance systems and existing alarm system are activated but most of the system is dedicated to it existing. In order to expand devices that is supported other monitoring function, separate device configuration or modification of integrated surveillance system are inevitable. In this study, interface standard between standard controller, integrated command center and each device that facilitate additional expansion of integrated surveillance system and avoid the extra cost is presented.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.6
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• pp.786-791
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• 2007

In the place that its security is crucial, the necessity of system which can tract and recognize random person is getting more important. In this paper, we'd like to develop the invader tracking system which consists of the sound source tracking-sensor and the pan-tilt camera for wide-area guard. After detecting the direction of any sound with the sound source tracking-sensor at first, our system make move the pan-tilt camera to that direction and extract reference image from that camera. This reference image is compared and updated by the next captured image after some interval time. By keeping on it over again, we can realize the guard system which can tract an invader using the difference image and the result of another image processing. By linking home network security system, the suggested system can provide some interfacing functions for the security service of the public facilities as well as that of home.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.741-747
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• 2012

In this paper, we propose a fast and robust framework for detecting and tracking multiple targets. The proposed system includes two modules: object detection module and object tracking module. In the detection module, we preprocess the input images frame by frame, such as gray and binarization. Next after extracting the foreground object from the input images, morphology technology is used to reduce noises in foreground images. We also use a block-based histogram analysis method to distinguish human and other objects. In the tracking module, color-based tracking algorithm and Kalman filter are used. After converting the RGB images into HSV images, the color-based tracking algorithm to track the multiple targets is used. Also, Kalman filter is proposed to track the object and to judge the occlusion of different objects. Finally, we show the effectiveness and the applicability of the proposed method through experiments.

• Spatial Information Research
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• v.21 no.3
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• pp.11-19
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• 2013

Compared with traditional video monitoring systems that provide a video-recording function as a main service, an intelligent video monitoring system is capable of extracting/tracking objects and detecting events such as car accidents, traffic congestion, pedestrian detection, and so on. Thus, the object tracking is an essential function for various intelligent video monitoring and surveillance systems. In this paper, we propose a background and local histogram-based object tracking approach for intelligent video monitoring systems. For robust object tracking in a live situation, the result of optical flow and local histogram verification are combined with the result of background subtraction. In the proposed approach, local histogram verification allows the system to track target objects more reliably when the local histogram of LK position is not similar to the previous histogram. Experimental results are provided to show the proposed tracking algorithm is robust in object occlusion and scale change situation.

• Journal of Advanced Navigation Technology
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• v.27 no.6
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• pp.770-775
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• 2023

Recently, as the amount of digital data increases exponentially, the importance of data processing systems is being emphasized. In this situation, the selection and construction of data processing systems are becoming more important. In this study, the performance of cloud computing (CC), edge computing (EC), and UAV-based intelligent edge computing (UEC) was compared as a way to solve this problem. The characteristics, strengths, and weaknesses of each method were analyzed. In particular, this study focused on real-time large-capacity data processing situations such as corridor monitoring. When conducting the experiment, a specific scenario was assumed and a penalty was given to the infrastructure. In this way, it was possible to evaluate performance in real situations more accurately. In addition, the effectiveness and limitations of each computing method were more clearly understood, and through this, the help was provided to enable more effective system selection.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.330-335
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• 2001

The occurrences of occupational illness and injury have been seriously underestimated in Korea. Surveillance systems for occupational diseases have recently emerged as important strategies for the control of occupational hazards and the implementation of intervention programs to protect workers. However, health service providers do not actively diagnose occupational diseases and are unwilling to report occupational diseases. With the rapid growth of Internet usage in Korea, the computer network has become the predominant means of communicating and sharing information. Therefore, we developed a web-based updated information and education network to assist the health services providers in reporting occupational diseases. Information systems for occupational disease surveillance were also designed to support occupational disease reporting. Commonly available database systems, such as web databases, are useful to manage occupational diseases data efficiently. Standardized case definitions and report guidelines were also established, which included cumulative trauma disorder, occupational asthma, occupational contact dermatitis, and occupational cancer. This system may provide the basis of an efficient and continuously updated source of educational information and provide specific information concerning the occurrence of occupational diseases in specific areas. Background information on occupational diseases obtained in this way will be invaluable for preventing hazards and enforcing occupational disease prevention programs. Moreover, our experiences in establishing these information systems will be of great use in other countries and settings.