• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.3
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• pp.841-846
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• 2010

This paper presents design and implementation of an intelligent video surveillance system. The proposed system has advantages of management efficiency and operation robustness unrelated to working condition compared to conventional CCTV based system. The system hardware is designed and implemented by using commercial chips such as digital media processor and video encoder, video decoder and the functions of software are to analyze temperature distribution of a infrared image and to detect disaster situation such as fire. The required functions are confirmed by testing of the prototype and we verified practicality of the system.

• Journal of Advanced Navigation Technology
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• v.15 no.6
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• pp.1234-1240
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• 2011

Recently lots of problems are emerged on the conventional surveillance systems at several areas. Many research activities have been processing on those problems. Therefore, in this paper, it is helpful to all sorts of accident prevention and safe driving, and risks linked to the outside or the administrator tells, that intelligent video surveillance system which can be real-time analysis and monitoring configuration, technical elements, required features, application and its applies.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.07a
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• pp.42-45
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• 2010

This paper proposes an intelligent video surveillance system for human object tracking. The proposed system integrates the object extraction, human object recognition, face detection, and camera control. First, the object in the video signals is extracted using the background subtraction. Then, the object region is examined whether it is human or not. For this recognition, the region-based shape descriptor, angular radial transform (ART) in MPEG-7, is used to learn and train the shapes of human bodies. When it is decided that the object is human or something to be investigated, the face region is detected. Finally, the face or object region is tracked in the video, and the pan/tilt/zoom (PTZ) controllable camera tracks the moving object with the motion information of the object. This paper performs the simulation with the real CCTV cameras and their communication protocol. According to the experiments, the proposed system is able to track the moving object(human) automatically not only in the image domain but also in the real 3-D space. The proposed system reduces the human supervisors and improves the surveillance efficiency with the computer vision techniques.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.653-658
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• 2008

Service areas in the urban transit need to construct the intelligent integrated surveillance system, because they are the public places that many people get together at one time. In past, analogue, closed-circuit televisions and analogue video recorders are used to construct the surveillance system. Now, a lot parts of the analogue systems that depend on the images have been changed to the complicated system, which consists of sensors and images and also, to be digitalized. In past, the surveillance system was used as an inspection devices to examine the spots after happening some events. But, with a high level of the computer and communication technologies, it is possible that the digitalized data leads the intelligence systems to prevent some accidents by using the various analysis techniques. And the data could be used to decide surveillance policies and provide some information on the safety and management policies as well as surveillance policies. In this paper, we define the intelligent surveillance system and suggest the major functions of the system. Also, we suggest the fundamental functions that every part should get and describe the way to develop the system.

• Journal of the Korea Society of Computer and Information
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• v.25 no.6
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• pp.57-64
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• 2020

Video surveillance is consists of cameras, transmission devices, storage and playback devices, and is used for crime prevention and disaster monitoring. Recently, it has been spreading to a wide variety of fields, and has developed into an intelligent video surveillance system that can automatically recognize or track characteristic objects of people and things. The purpose of this study was to investigate the cases of video surveillance service applying the latest technology by dividing it into the home, public, and private sectors. also this study tried to investigate and research what advantage it brings from a business perspective. By looking at the cases introduced in this study, it was confirmed that the viedo security service is developing intelligently, such as excellent compatibility with CCTV, multiple video surveillance, CCTV screen motion detection, and alarm through automatic analysis.

• 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 Satellite, Information and Communications
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• v.10 no.2
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• pp.70-74
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• 2015

In this paper, satellite communication based video surveillance system that consisted of ultra-small aperture terminals with small-size smart vision sensor is proposed. The events such as forest fire, smoke, intruder movement are detected automatically in field and false alarms are minimized by using intelligent and high-reliable video analysis algorithms. The smart vision sensor is necessary to achieve high-confidence, high hardware endurance, seamless communication and easy maintenance requirements. To satisfy these requirements, real-time digital signal processor, camera module and satellite transceiver are integrated as a smart vision sensor-based ultra-small aperture terminal. Also, high-performance video analysis and image coding algorithms are embedded. The video analysis functions and performances were verified and confirmed practicality through computer simulation and vision sensor prototype test.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.4
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• pp.298-306
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• 2013

Recent years have witnessed a growing interest in the fields of video surveillance and mobile object tracking. This paper proposes a mobile object tracking algorithm. First, several parameters such as object window, object area, and expansion-contraction (E-C) parameter are defined. Then, a modified E-C algorithm for multiple-object tracking is presented. The proposed algorithm tracks moving objects by expansion and contraction of the object window. In addition, it includes methods for updating the background image and avoiding occlusion of the target image. The validity of the proposed algorithm is verified experimentally. For example, the first scenario traces the path of two people walking in opposite directions in a hallway, whereas the second one is conducted to track three people in a group of four walkers.

• Journal of Korea Multimedia Society
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• v.25 no.6
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• pp.807-818
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• 2022

In order to further improve the accuracy and time efficiency of behavior recognition in intelligent monitoring scenarios, a human behavior recognition algorithm based on YOLO combined with LSTM and CNN is proposed. Using the real-time nature of YOLO target detection, firstly, the specific behavior in the surveillance video is detected in real time, and the depth feature extraction is performed after obtaining the target size, location and other information; Then, remove noise data from irrelevant areas in the image; Finally, combined with LSTM modeling and processing time series, the final behavior discrimination is made for the behavior action sequence in the surveillance video. Experiments in the MSR and KTH datasets show that the average recognition rate of each behavior reaches 98.42% and 96.6%, and the average recognition speed reaches 210ms and 220ms. The method in this paper has a good effect on the intelligence behavior recognition.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.6
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• pp.161-169
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• 2011

Recent intelligent video surveillance system asks for development of more advanced technology for analysis and recognition of video data. Especially, machine learning algorithm such as Support Vector Machine (SVM) is used in order to recognize objects in video. Because SVM training demands massive amount of computation, parallel processing technique is necessary to reduce the execution time effectively. In this paper, we propose a parallel processing method of SVM training with a multi-core processor. The results of parallel SVM on a 4-core processor show that our proposed method can reduce the execution time of the sequential training by a factor of 2.5.