• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.2
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• pp.69-78
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• 2024

Recently, the use of CCTV to prevent crowd accidents has been promoted, but research is needed to compensate for the spatial limitations of CCTV. In this study, pedestrian density was measured using drone footage, and based on a review of existing literature, a threshold of 6.7 people/m² was selected as the cutoff risk level for crowd accidents. In addition, we conducted a preliminary study to determine drone parameters and found that the pedestrian recognition rate was high at a drone altitude of 20 meters and an angle of 60°. Based on a previous study, we selected a target area with a high concentration of pedestrians and measured pedestrian density, which was found to be 0.27~0.30 per m². The study shows it is possible to measure risk levels by determining pedestrian densities in target areas using drone images. We believe drone surveillance will be utilized for crowd safety management in the near future.

• Journal of Internet Computing and Services
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• v.18 no.4
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• pp.61-67
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• 2017

Recently, CCTV has been combined with areas such as big data, artificial intelligence, and image analysis to detect various abnormal behaviors and to detect and analyze the overall situation of objects such as people. Image analysis research for this intelligent video surveillance function is progressing actively. However, CCTV images using 2D information generally have limitations such as object misrecognition due to lack of topological information. This problem can be solved by adding the depth information of the object created by using two cameras to the image. In this paper, we perform background modeling using Mixture of Gaussian technique and detect whether there are moving objects by segmenting the foreground from the modeled background. In order to perform the depth information-based segmentation using the RGB information-based segmentation results, stereo-based depth maps are generated using two cameras. Next, the RGB-based segmented region is set as a domain for extracting depth information, and depth-based segmentation is performed within the domain. In order to detect the center point of a robustly segmented object and to track the direction, the movement of the object is tracked by applying the CAMShift technique, which is the most basic object tracking method. From the experiments, we prove the efficiency of the proposed object detection and tracking method using the RGB-D model.

• ETRI Journal
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• v.44 no.2
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• pp.183-193
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• 2022

Smart cities are expected to provide residents with convenience via various agents such as CCTV, delivery robots, security robots, and unmanned shuttles. Environmental data collected by various agents can be used for various purposes, including advertising and security monitoring. This study suggests a surveillance map data framework for efficient and integrated multimodal data representation from multi-agents. The suggested surveillance map is a multilayered global information grid, which is integrated from the multimodal data of each agent. To confirm this, we collected surveillance map data for 4 months, and the behavior patterns of humans and vehicles, distribution changes of elevation, and temperature were analyzed. Moreover, we represent an anomaly detection algorithm based on a surveillance map for security service. A two-stage anomaly detection algorithm for unusual situations was developed. With this, abnormal situations such as unusual crowds and pedestrians, vehicle movement, unusual objects, and temperature change were detected. Because the surveillance map enables efficient and integrated processing of large multimodal data from a multi-agent, the suggested data framework can be used for various applications in the smart city.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.545-547
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• 2020

기존의 침임자 대응방식을 보완하기 위해 지능형 관제 시스템과 CCTV 와 다수의 로봇들을 이용하여 객체 인식을 통해 침입자를 인식하고 추적하여 침입자의 좌표를 전송하고 시야에서 사라진 침입자의 위치를 추정하여 로봇들이 침입자의 퇴로를 차단하고 알고리즘을 통해 추정되는 위치를 순찰하며 침입자를 찾아내는 경비 시스템이다.

• 한국ITS학회지
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• v.1 no.1
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• pp.69-73
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• 2003

A transportation problem is a serious theme to be solved urgently in the motor era of 20 million vehicles. Recently ITS has been introduced to optimize the efficiency of the current roads, because a excess budget and a long term construction are necessary to build new roads. In this paper an outline and major systems of ITS for Ulsan metropolitan city are presented.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10b
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• pp.544-548
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• 2006

본 논문에서는 광범위한 지역을 감시하기 위해 설치된 여러 대의 카메라로부터 획득된 비디오에 대해 물체를 기반으로 한 비디오 요약 시스템을 제안한다. 제안된 시스템은 시야가 겹쳐지지 않은 다수의 CCTV 카메라를 통해서 촬영한 비디오들을 30분 단위로 나누어 비디오 데이터베이스를 구축하고 시간별, 카메라별 비디오 검색이 가능하다. 비디오에서 물체기반 키프레임을 추출하여 카메라별, 사람별로 비디오를 요약할 수 있도록 하였다. 또한 임계치에 따라 키프레임 검색정도를 조절함으로써 비디오 요약정도를 조절할 수 있다. 이렇게 검색된 키프레임에 대한 카메라별, 시간별 통계를 통해서 감시지역의 물체기반 이벤트를 간단히 확인해 볼 수 있다.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.6
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• pp.577-582
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• 2013

In this paper, the state-of-the-art IVEF Service based on e-Navigation System was represented. The unification of the data exchange format among maritime-related systems is one of vital user-needs of e-Navigation, advantageous in bringing maritime safety and security. This paper propose the method to exchange marine information in IVEF, as recommended by the IALA, between VTS centers and Korea's GICOMS as well as the government-related agencies. To achieve this, a system data flow was designed which it acts as client and server. It enables the sending and receiving of Radar and CCTV images in accordance with the IVEF recommendation document of IALA.

• IEIE Transactions on Smart Processing and Computing
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• v.3 no.3
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• pp.128-134
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• 2014

A real-time, continuous-scale image interpolation method is proposed based on a bilinear interpolation with directionally adaptive low-pass filtering. The proposed algorithm was optimized for hardware implementation. The ordinary bi-linear interpolation method has blocking artifacts. The proposed algorithm solves this problem using directionally adaptive low-pass filtering. The algorithm can also solve the severe blurring problem by selectively choosing low-pass filter coefficients. Therefore, the proposed interpolation algorithm can realize a high-quality image scaler for a range of imaging systems, such as digital cameras, CCTV and digital flat panel displays.

• Proceedings of the KSR Conference
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• 2005.11a
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• pp.915-920
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• 2005

Passenger safety is a primary concern of railway system but, it has been urgent issue that dozens of people are killed every year when they fall off from train platforms. Recently, advancements in IT have enabled applying vision sensors to railway environments, such as CCTV and various camera sensors. The objective of this work is to propose technical and system requirements for establishing intelligent monitoring system using camera equipments in urban transit system. We suppose the system is to determine automatically and in real-time whether anyone or anything is in monitoring area. To achieve the goal, we analyze recent image processing technologies for detection and recognition, and suggest possible direction of system development for applying urban transit system. According to the results, we expect the proposed system requirements will playa key role for establishing highly intelligent monitoring system in railway.

• Journal of KIISE
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• v.43 no.12
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• pp.1351-1355
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• 2016

The number of CCTV units is rapidly increasing annually, and the demand for intelligent video-analytics system is also increasing continuously for the effective monitoring of them. The existing analytics engines, however, require considerable computing resources and cannot provide a sufficient detection accuracy. For this paper, a light analytics engine was employed to analyze video and we collected metadata, such as an object's location and size, and the dwell time from the engine. A further data analysis was then performed to filter out the target of interest; as a result, it was possible to verify that a light engine and the heavy data analytics of the metadata from that engine can reject an enormous amount of environmental noise to extract the target of interest effectively. The result of this research is expected to contribute to the development of active intelligent-monitoring systems for the future.