• International journal of advanced smart convergence
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• v.10 no.2
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• pp.45-52
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• 2021

The surveillance camera market has developed and plays an important role in the field of video surveillance. However, in recent years, the identification of areas requiring surveillance has been limited by reflective light in the surveillance camera market. Cameras using polarization filters are being developed to reduce reflective light and facilitate identification. Programs are required to automatically adjust polarization filters. In this paper, we proposed an optimal angle extraction method from surveillance cameras using polarization filters through histogram analysis. First of all, transformed to grayscale to analyze the specifications of frames in multiple polarized angle images, reducing computational throughput. Then we generated and analyzed a histogram of the corresponding frame to extract the angle when the highlights are the fewest. Experiments with 0˚ and 90˚ showed high performance in extracting optimal angles. At this point, it is hoped this technology would be used for surveillance cameras in place like beach with a lot of reflective light.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2020.11a
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• pp.55-56
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• 2020

The construction industry has the highest occupational fatality and injury rates related to accidents of any industry. Accordingly, safety managers closely monitor to prevent accidents in real-time by installing surveillance cameras at construction sites. However, due to human cognitive ability limitations, it is impossible to monitor many videos simultaneously, and the fatigue of the person monitoring surveillance cameras is also very high. Thus, to help safety managers monitor work and reduce the occupational accident rate, a study on object recognition in construction sites was conducted through surveillance cameras. In this study, we applied to the instance segmentation to identify the classification and location of objects and extract the size and shape of objects in construction sites. This research considers ways in which deep learning-based computer vision technology can be applied to safety management on a construction site.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.628-631
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• 2003

In this paper, we present real-time, accurate face region detection and tracking technique for an intelligent surveillance system. It is very important to obtain the high-resolution images, which enables accurate identification of an object-of-interest. Conventional surveillance or security systems, however, usually provide poor image quality because they use one or more fixed cameras and keep recording scenes without any cine. We implemented a real-time surveillance system that tracks a moving person using four pan-tilt-zoom (PTZ) cameras. While tracking, the region-of-interest (ROI) can be obtained by using a low-pass filter and background subtraction. Color information in the ROI is updated to extract features for optimal tracking and zooming. The experiment with real human faces showed highly acceptable results in the sense of both accuracy and computational efficiency.

• International journal of advanced smart convergence
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• v.9 no.4
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• pp.120-123
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• 2020

The surveillance system to prevent crime and accidents in advance has become a necessity, not an option in real life. Not only public institutions but also individuals are installing surveillance cameras to protect their property and privacy. However, since the installed surveillance camera cannot be monitored for 24 hours, the focus is on the technology that tracks the video after an accident occurs rather than prevention. In this paper, we propose a system model that monitors abnormal behaviors that may cause crimes through real-time video, and when a specific behavior occurs, the surveillance system automatically detects it and responds immediately through an alarm. We are a model that analyzes real-time images from surveillance cameras and uses I3D models from analysis servers to analyze abnormal behavior and deliver notifications to web servers and then to clients. If the system is implemented with the proposed model, immediate response can be expected when a crime occurs.

• Asia-Pacific Journal of Business
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• v.14 no.4
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• pp.49-65
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• 2023

Purpose - In the Korean and Chinese social landscape, it is vital to appreciate the significance of the Japanese history problem. The current study investigated whether the perception of the Japanese history problem affects decisions regarding technology adoption in organizations by comparing South Korea and China. Design/methodology/approach - The study involved 305 Korean and 379 Chinese participants who responded to scenarios and surveys regarding the adoption of workplace surveillance cameras supplied by a Japanese company. Findings - Using a moderated mediation model based on protection motivation theory (PMT), we found that past experiences of privacy invasion significantly reduced trust in the adoption of surveillance cameras at work. This relationship was mediated by respondents' perceptions of security vulnerability. The current study, however, did not confirm any significant moderating effect of the Japanese history problem priming on trust in the adoption of workplace surveillance cameras. Research implications - This suggests that the Japanese history problem may have a limited impact on organizational technology adoption decisions, different from the political consumerism behavior driven by public anti-Japanese affectivity. The current study reaffirms the validity and applicability of PMT and provides both theoretical insights and practical recommendations.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1187-1188
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• 2007

Most of the surveillance systems are based on CCTV, closed circuit Television. A surveillance system for urban transit is also based on CCTV. Urban transit operation corporations have a CCTV system and a lot of cameras to monitor the situation for the passengers, and the important facilities. But this system has some problems that it cannot respond to a state of emergency immediately. In this paper, we describe a configuration of an intelligent surveillance system for urban transit to solve that problems. Our proposed configuration include a camera with some intelligent module, and a processor to integrate various data from not only cameras, but also sensors such as a temperature sensor, a heat sensor, sound sensor and etc. and some other data generator. This system configuration can decide the state of the passengers and the facilities. The surveillance system with this configuration can available with the existing surveillance system without a considerable improvement.

• Journal of Information Processing Systems
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• v.15 no.2
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• pp.344-358
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• 2019

Surveillance cameras have installed in many places because security and safety is becoming important in modern society. Through surveillance cameras installed, we can deal with troubles and prevent accidents. However, watching surveillance videos and judging the accidental situations is very labor-intensive. So now, the need for research to analyze surveillance videos is growing. This study proposes an algorithm to track multiple persons using SURF and background subtraction. While the SURF algorithm, as a person-tracking algorithm, is robust to scaling, rotating and different viewpoints, SURF makes tracking errors with sudden changes in videos. To resolve such tracking errors, we combined SURF with a background subtraction algorithm and showed that the proposed approach increased the tracking accuracy. In addition, the background subtraction algorithm can detect persons in videos, and SURF can initialize tracking targets with these detected persons, and thus the proposed algorithm can automatically detect the enter/exit of persons.

• Smart Structures and Systems
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• v.25 no.5
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• pp.531-541
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• 2020

This paper demonstrates the possibility of evaluating the safety of a building right after an earthquake using consumer-grade surveillance cameras installed in the building. Two cameras are used in each story to extract the time history of interstory drift during the earthquake based on camera calibration, stereo triangulation, and image template matching techniques. The interstory drift of several markers on the rigid floor are used to estimate the motion of the geometric center using the least square approach, then the horizontal interstory drift of any location on the floor can be estimated. A shaking table collapse test of a steel building was conducted to verify the proposed approach. The results indicate that the accuracy of the interstory drift measured by the cameras is high enough to estimate the damage state of the building based on the fragility curve of the interstory drift ratio. On the other hand, the interstory drift measured by an accelerometer tends to underestimate the damage state when residual interstory drift occurs because the low frequency content of the displacement signal is eliminated when high-pass filtering is employed for baseline correction.

• Journal of IKEEE
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• v.17 no.2
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• pp.104-110
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• 2013

In this paper, we introduce a smart care surveillance system which can support various CCTV cameras. In order to monitor an emergency requester in case of emergency, the server performs automatical CCTV Pan, Tilt, and Zoom control based on the location coordinates of the emergency requester. Also, a server finds and tracks the emergency requester using image processing and the updated location information. We implement a smart care surveillance system using the Genetec SDK tool to support various CCTV cameras. The efficiency of the rescue operation with the smart care surveillance system can be improved because rescuer can quickly control and monitor the requester's CCTV images.

• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.5
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• pp.813-827
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• 2017

Surveillance cameras installed in tunnels capture the various video frames effected by dynamic and variable factors. In addition, localizing and managing the cameras in tunnel is not affordable, and quality of capturing frame is effected by time. In this paper, we introduce a new method to detect and track the vehicles in tunnel by using surveillance cameras installed in a tunnel. It is difficult to detect the video frames directly from surveillance cameras due to the motion blur effect and blurring effect on lens by dirt. In order to overcome this difficulties, two new methods such as Differential Frame/Non-Maxima Suppression (DFNMS) and Haar Cascade Detector to track cars are proposed and investigated for their feasibilities. In the study, it was shown that high precision and recall values could be achieved by the two methods, which then be capable of providing practical data and key information to an automatic accident detection system in tunnels.