• Korean Institute of Interior Design Journal
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• v.22 no.6
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• pp.40-48
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• 2013

Utilization of CCTV in crime prevention for public safety is accepted as the most effective measure in terms of crime prevention and control. Also, it is frequently used as a device that shows evidence of an unexpected situation or record on public social relationship. However, it is rare to find a study that qualitatively accessed the monitoring performance of a certain space depending on the choice and positioning of CCTVs. Thus, this study suggested a technology that can quantitatively compare and assess the monitoring performance of CCTVs depending on view angle and effective sight range of cameras as well as the monitoring performance depending on positioning measures. For the analysis, the concept of 3-dimensional surveillance field in the form of a frustum was suggested while deriving 3-dimensional range of sight and quantitative monitoring performance by applying Isovist theory. For the analysis technology, space of analysis subject, point of view (camera), and target point (measurement node) were installed at a 3-dimensional space and in use of ray-tracing algorithm, the line segment that was visually connected between the point of view and target point was extracted and accumulated. For such verification, analysis application was constructed and then applied to four alternative models on view angle and distance as well as four alternatives on positioning in order to verify its efficacy. Through the experiment, it was possible to compare and assess visibility depending on alternatives while quantifying the results by understanding the shadow areas beyond the monitoring range.

• Journal of Internet of Things and Convergence
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• v.5 no.1
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• pp.7-11
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• 2019

This study suggests a methodology to track crime suspects or anomalies through CCTV in order to expand the scope of CCTV use as the number of CCTV installations continues to increase nationwide in recent years. For the abnormal behavior classification, we use the existing studies to find out suspected criminals or abnormal actors, use CNN to track objects, and connect the surrounding CCTVs to each other to predict the movement path of objectified objects CCTVs in the vicinity of the path were used to share objects' sample data to track objects and to track objects. Through this research, we will keep track of criminals who can not be traced, contribute to the national security, and continue to study them so that more diverse technologies can be applied to CCTV.

• Journal of Internet Computing and Services
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• v.21 no.5
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• pp.109-118
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• 2020

Recently, people are spending a lot of time inside their homes because of various diseases. It is difficult to ask others for help in the case of a single-person household that is injured in the house or infected with a disease and needs help from others. In this study, an algorithm is proposed to detect emergency event, which are situations in which single-person households need help from others, such as injuries or disease infections, in their homes. It proposes vision pattern detection algorithms using home CCTVs, audio pattern detection algorithms using artificial intelligence speakers, activity pattern detection algorithms using acceleration sensors in smartphones, and dust pattern detection algorithms using air purifiers. However, if it is difficult to use due to security issues of home CCTVs, it proposes a fusion method combining audio, activity and dust pattern sensors. Each algorithm collected data through YouTube and experiments to measure accuracy.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.5
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• pp.195-205
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• 2020

Recently, after the 4th industrial revolution era has arrived, technological advances started to develop and these changes have led to widespread use of data. Big data is often used for the safety of citizens, including the administration, safety and security of the country. In order to enhance the efficiency of maintaining such security, it is necessary to understand the installation status of CCTVs. By comparing the installation rate of CCTVs and crime rate in the area, we should analyze and improve the status of CCTV installation status, and crime rate in each area in order to increase the efficiency of security. Therefore, in this paper, big data analytic system based on public data is developed to collect data related to crime rate such as CCTV, female population, entertainment center, etc. and to reduce crime rate through efficient management and installation of CCTV.

• Journal of the Korea Society of Computer and Information
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• v.24 no.8
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• pp.19-28
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• 2019

In this paper, an online video summarization algorithm based on multiple object detection is proposed. As crime has been on the rise due to the recent rapid urbanization, the people's appetite for safety has been growing and the installation of surveillance cameras such as a closed-circuit television(CCTV) has been increasing in many cities. However, it takes a lot of time and labor to retrieve and analyze a huge amount of video data from numerous CCTVs. As a result, there is an increasing demand for intelligent video recognition systems that can automatically detect and summarize various events occurring on CCTVs. Video summarization is a method of generating synopsis video of a long time original video so that users can watch it in a short time. The proposed video summarization method can be divided into two stages. The object extraction step detects a specific object in the video and extracts a specific object desired by the user. The video summary step creates a final synopsis video based on the objects extracted in the previous object extraction step. While the existed methods do not consider the interaction between objects from the original video when generating the synopsis video, in the proposed method, new object clustering algorithm can effectively maintain interaction between objects in original video in synopsis video. This paper also proposed an online optimization method that can efficiently summarize the large number of objects appearing in long-time videos. Finally, Experimental results show that the performance of the proposed method is superior to that of the existing video synopsis algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.1
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• pp.22-27
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• 2020

Recently, as the number of households raising pets increases due to the increase of single households, there is a need for a system for monitoring the status or behavior of pets. There are regional limitations in the monitoring of pets using domestic CCTVs, which requires a large number of CCTVs or restricts the behavior of pets. In this paper, we propose a mobile system for detecting and tracking cats using deep learning to solve the regional limitations of pet monitoring. We use YOLO (You Look Only Once), an object detection neural network model, to learn the characteristics of pets and apply them to Raspberry Pi to track objects detected in an image. We have designed a mobile monitoring system that connects Raspberry Pi and a laptop via wireless LAN and can check the movement and condition of cats in real time.

• Journal of Advanced Navigation Technology
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• v.27 no.3
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• pp.287-292
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• 2023

In the case of fixed CCTV, there is a problem in that a shadow area occurs, even if the visible range is maximized by utilizing the pan-tilt and zoom functions. The representative solution for that problem is that a plurality of fixed CCTVs are used. This requires a large amount of additional equipment (e.g., wires, facilities, monitors, etc.) proportional to the number of the CCTVs. Another solution is to use drones that are equipped with cameras and fly. However, Drone's operation time is much short. In order to extend the time, we can use multiple drones and can fly one by one. In this case, drones that need to recharge their batteries re-enter into a ready state at the drone port for next operation. In this paper, we propose a system for precised positioning and stable landing on the drone port by utilizing a small drone equipped with a fixed forward-facing monocular camera. For our conclusion, we implement our proposed system, operate, and finally verify our feasibility.

• The Korean Society of Law and Medicine
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• v.22 no.2
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• pp.111-138
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• 2021

'Unlicensed medical practice by a non-medical practitioner' often represented by surrogate surgery or so-called 'ghost surgery,' causes irreparable damage to life or body, and therefore calls for very strict and effective controls. The 'bill on installment of CCTVs in an operating room' to prevent unlicensed surrogate surgery has been discussed for a long time, but due to numerous issues and heated confrontations, it has been pending in the National Assembly. Nevertheless, it is expected that the bill will be discussed again in earnest in the National Assembly because surrogate surgery and factory-type cosmetic surgery, which has been performed mainly in the field of cosmetic surgery, has also been occurring in the field of therapeutic surgery. In general, an operating room is considered as being locked or closed, as well as disallowing implicit complicity among insiders. Hence, if the insiders conspire to commit or cover up an illegal act, or if a surgeon performs rapid cosmetic surgery and then leaves the recipient (or medical institution) so as to perform more operations for profit - even if it is legitimate practice - it may result in serious consequences in terms of the recovery of a patient. In this case, installation of CCTVs can be of great help in identifying an illegal act and assessing any occurrence of negligence. On the other hand, while the fundamental purpose of therapeutic surgery is to restore a patient's life or body - that is, lifesaving - installation of CCTVs may base the relationship between a surgeon and a patient on distrust and surveillance, so it may increase the number of requests for CCTV footage or lead to more disputes, as well as placing a burden on the surgeon when best results are not achieved for a patient. As a result, the surgeon may choose non-invasive treatment contrary to conscience instead of risky but necessary surgery, or he/she may have significant difficulty in determining the timing of surgery, which may limit the provision of effective surgical medical care. Then, in terms of the relationship between a surgeon and patient, and in the long run, there could be significant disadvantages for the public and patients if CCTV footage is allowed. In this paper, we review domestic and overseas cases and issues regarding installation of CCTVs in an operating room, and present various viewpoints and suggestions to promote legislation with minimized legal problems and side effects, thereby contributing to protection of the lives and health of the public, patients, and recipients of surgery.

• International Journal of Contents
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• v.7 no.4
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• pp.19-23
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• 2011

This paper proposes a segmentation method for overlapped vehicles based on analysis of the vehicle location and the spatiotemporal association information. This method can be used in an intelligent transport system. In the proposed method, occlusion is detected by analyzing the association information based on a vehicle's location in continuous images, and occlusion segmentation is carried out by using the vehicle information prior to occlusion. In addition, the size variations of the vehicle to which association tracking is applied can be anticipated by learning the variations according to the overlapped vehicles' movements. To assess the performance of the suggested method, image data collected from CCTVs recording traffic information is used, and average success rate of occlusion segmentation is 96.9%.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.3
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• pp.153-163
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• 2016

Local feature extraction methods for images and videos are widely applied in the fields of image understanding and computer vision. However, robust features are detected differently when using the latest feature detectors and descriptors because of diverse image environments. This paper analyzes various feature extraction methods by summarizing algorithms, specifying properties, and comparing performance. We analyze eight feature extraction methods. The performance of feature extraction in various image environments is compared and evaluated. As a result, the feature detectors and descriptors can be used adaptively for image sequences captured under various image environments. Also, the evaluation of feature detectors and descriptors can be applied to driving assistance systems, closed circuit televisions (CCTVs), robot vision, etc.