• 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 the Institute of Electronics Engineers of Korea SP
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• v.42 no.5 s.305
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• pp.79-84
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• 2005

In this paper, we developed an omni-directional surveillance and motion detection method. The fish-eye lens provides a wide field of view image. Using this image, the equi-distance model for the fish-eye lens is applied to get the perspective and panorama images. Generally, we must consider the trade-off between resolution and field of view of an image from a camera. To enhance the resolution of the result images, some kind of interpolation methods are applied. Also the moving edge method is used to detect moving objects for the object tracking.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.7
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• pp.1421-1426
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• 2003

In this paper, we implement a picture surveillance system using IBM-compatible PC with web camera. The reflex RGB data captured from WebCam is stored to HDD through USB port at every 5 seconds intervals. Also, if strangers are detected through Motion Detection routine, warning voice message is broadcasted and invasion message is transmitted by e-mail and transmit the e-mail title to mobile phone through WAP(Wireless Application Protocol) push. The detected image is stored to hard-disk in ‘month-day-hour-minute-second. jpg’ data type. And the image data is transmitted to web server through FTP(File Transfer Protocol) because invader can deletes or destroys the image data on hard-disk We implement a surveillance system which is able to utilize through internet regardless of time and space.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.699-701
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• 2010

For the development of surveillance Multi Sensor and IFOG, development of integrated surveillance camera for day and night time of its system Control Unit design and navigation device interlocking system was made. Control Unit analysis of integrated ship system began with selection of control unit related to feasible navigation device list.After sorting navigation equipment list, applications, features, connection methods, communication methods, data type of control unit and data direction between navigation equipments and the data types of each navigation equipment is sorted to observe its performance.

• ETRI Journal
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• v.41 no.4
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• pp.494-505
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• 2019

In this paper, we propose a new framework for detecting the unauthorized dumping of garbage in real-world surveillance camera. Although several action/behavior recognition methods have been investigated, these studies are hardly applicable to real-world scenarios because they are mainly focused on well-refined datasets. Because the dumping actions in the real-world take a variety of forms, building a new method to disclose the actions instead of exploiting previous approaches is a better strategy. We detected the dumping action by the change in relation between a person and the object being held by them. To find the person-held object of indefinite form, we used a background subtraction algorithm and human joint estimation. The person-held object was then tracked and the relation model between the joints and objects was built. Finally, the dumping action was detected through the voting-based decision module. In the experiments, we show the effectiveness of the proposed method by testing on real-world videos containing various dumping actions. In addition, the proposed framework is implemented in a real-time monitoring system through a fast online algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.25-27
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• 2021

With the recent development of deep learning technology, computer vision-based AI technologies have been studied to analyze the abnormal behavior of objects in image information acquired through CCTV cameras. There are many cases where surveillance cameras are installed in dangerous areas or security areas for crime prevention and surveillance. For this reason, companies are conducting studies to determine major situations such as intrusion, roaming, falls, and assault in the surveillance camera environment. In this paper, we propose a real-time abnormal behavior analysis algorithm using object detection and tracking method.

• Journal of Korea Game Society
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• v.7 no.4
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• pp.63-70
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• 2007

Since the fisheye lens has a wide field of view, it can capture the scene and illumination from all directions from far less number of omnidirectional images. Due to these advantages of the omnidirectional camera, it is widely used in surveillance and reconstruction of 3D structure of the scene In this paper, we present a new self-calibration algorithm of omnidirectional camera from uncalibrated images by considering the inlier distribution. First, one parametric non-linear projection model of omnidirectional camera is estimated with the known rotation and translation parameters. After deriving projection model, we can compute an essential matrix of the camera with unknown motions, and then determine the camera information: rotation and translations. The standard deviations are used as a quantitative measure to select a proper inlier set. The experimental results showed that we can achieve a precise estimation of the omnidirectional camera model and extrinsic parameters including rotation and translation.

• IEMEK Journal of Embedded Systems and Applications
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• v.11 no.1
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• pp.21-27
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• 2016

An integrated display software platform for small UAV is developed based on parallel processing technique in this paper. When the small UAV with high-performance camera and avionic modules is employed to various surveillance-related missions, it is important to reduce the operator's workload and increase the monitoring efficiency. For this purpose, it is needed to develop an efficient monitoring software enable to manipulate the image and flight data obtained during flight within the given processing time and display them simultaneously. In this paper, we set up requirements and suggest the architecture for the software platform. The integrated software platform is implemented with parallel processing scheme. Based on AR drone, we verified that the various data are concurrently displayed by the suggest software platform.

• Journal of Electrical Engineering and Technology
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• v.10 no.1
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• pp.372-378
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• 2015

Background subtraction is the first processing stage in video surveillance. It is a general term for a process which aims to separate foreground objects from a background. The goal is to construct and maintain a statistical representation of the scene that the camera sees. The output of background subtraction will be an input to a higher-level process. Background subtraction under dynamic environment in the video sequences is one such complex task. It is an important research topic in image analysis and computer vision domains. This work deals background modeling based on modified adaptive Gaussian mixture model (GMM) with three temporal differencing (TTD) method in dynamic environment. The results of background subtraction on several sequences in various testing environments show that the proposed method is efficient and robust for the dynamic environment and achieves good accuracy.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.1211-1212
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• 2008

In this paper, we propose image process modeling as a part of location based surveillance system for unauthorized target recognition and tracking in harbor, airport, military zone. For this, we compress and store background image in lower resolution and perform object extraction and motion tracking by using sobel edge detection and difference picture method between real images and a background image. In addition to, we use Independent Component Analysis Neural Network for moving target recognition. Experiments are performed for object extraction and tracking of moving targets on road by using static camera in 20m height building and it shows the robust results.