• Journal of Ocean Engineering and Technology
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• v.27 no.3
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• pp.22-28
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• 2013

This paper suggests a navigation information display system that is based on augmented reality technology. A navigator always has to confirm the information from marine electronic navigation devices and then compare it with the view of targets outside the windows. This "head down" posture causes discomfort and sometimes near accidents such as collisions or missing objects, because he or she cannot keep an eye on the front view of the windows. Augmented reality can display both virtual and real information in a single display. Therefore, we attempted to adapt AR technology to assist navigators. To analyze the outside view of the bridge window, various computer image processing techniques are required because the sea surface has many noises that disturb computer image processing for object detection, such as waves, wakes, light reflection, and so on. In this study, we investigated an analysis module to extract navigational information from images that are captured by a CCTV camera, and we validated our prototype.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.418-427
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• 2016

A smart parking management requires to track a vehicle in a indoor parking lot and to detect the place where the vehicle is parked. An advanced parking system watches all space of the parking lot with CCTV cameras. We can use these cameras for vehicles tracking and detection. In order to cover a wide area with a camera, a fisheye lens is used. In this case the shape and size of an moving vehicle vary much with distance and angle to the camera. This makes vehicle detection and tracking difficult. In addition to the fisheye lens, the vehicle headlights also makes vehicle detection and tracking difficult. This paper describes a method of realtime vehicle detection and tracking robust to the harsh situation described above. In each image frame, we update the region of a vehicle and estimate the vehicle movement. First we approximate the shape of a car with a quadrangle and estimate the four sides of the car using multiple histograms of oriented gradient. Second we create a template by applying a distance transform to the car region and estimate the motion of the car with a template matching method.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.264-270
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• 2016

In this paper, we proposed a method which can detect pedestrians from CCTV video and estimate the height of the detected objects. We separate the foreground using Gaussian mixture model and the pedestrian is detected using the conditions such as the width-height ratio and the size of the candidate objects. In order to obtain the optimal model for estimating the height of pedestrian, we get many training data from the pedestrian whose height is known. Using these training data, we designed optimal Wiener height estimator and used to estimate the height of pedestrians. The height of the pedestrian at various distance is estimated and the accuracy is evaluated. In the experimental results, proposed method shows that it can estimate the height of pedestrian for various positions effectively.

• Journal of Information Technology Services
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• v.15 no.3
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• pp.71-95
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• 2016

In recent years, text mining has been used to extract meaningful insights from the large volume of unstructured text data sets of various domains. As one of the most representative text mining applications, topic modeling has been widely used to extract main topics in the form of a set of keywords extracted from a large collection of documents. In general, topic modeling is performed according to the weighted frequency of words in a document corpus. However, general topic modeling cannot discover the relation between documents if the documents share only a few terms, although the documents are in fact strongly related from a particular perspective. For instance, a document about "sexual offense" and another document about "silver industry for aged persons" might not be classified into the same topic because they may not share many key terms. However, these two documents can be strongly related from the R&D perspective because some technologies, such as "RF Tag," "CCTV," and "Heart Rate Sensor," are core components of both "sexual offense" and "silver industry." Thus, in this study, we attempted to discover the differences between the results of general topic modeling and R&D perspective topic modeling. Furthermore, we package social issues from the R&D perspective and present a prototype system, which provides a package of news articles for each R&D issue. Finally, we analyze the quality of R&D perspective topic modeling and provide the results of inter- and intra-topic analysis.

• Journal of the Korean housing association
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• v.22 no.6
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• pp.71-82
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• 2011

Recently the crime against elementary school students has been rapidly increasing. Under these circumstances, this study is to analyze the basic principles of Crime Prevention Through Environmental Design (CPTED) for the elementary school in urban residential area, and suggest some planning and design guidelines. Among 59 elementary schools in Pyongchon, Bundang, and Pangyo new towns, 11 distinctive schools were selected for analysis study. School cases were investigated comparatively from the viewpoints of visibility, securing of observers, activity support and reinforced territoriality on the basis of theoretical crime prevention concepts. The analysis adopts various methods including theoretical research, field study, observation, and examination of plan. Some of findings of this analysis are as follows. Most of schools rely on the mechanical and physical devices such as CCTV, gate control, or walls, which are considered to be quite passive measures and ineffective for the crime prevention. Other effective methods such as offering school facilities to the public or public space sharing with surrounding residents, for the protection of crimevulnerable students by public eyes. Therefore, in order to prevent crimes effectively, it is urgently required to analyze the environments around and in the school, and to improve physical conditions on the basis of CPTED principles.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.66 no.4
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• pp.252-257
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• 2017

In this paper for developing and implementing the HD level triple streaming hybrid security camera which output the three type of video outputs(HD-SDI, EX-SDI, Analog). We design the hardware and program the firmware supporting the main and sub functions. We use MN34229PL as image sensor, EN778, EN331 as image processor, KA909A as reset, iris, day&night function part, A3901SEJTR-T as zoom/focus control part. We request the performance test of developed security camera at the broadcasting and communication fusion testing department of TTA (Telecommunication Technology Association). We can get the three outputs (HD-SDI, EX-SDI, Analog) from the developed security camera, get the world best level at the jitter and eye pattern amplitude value and exceed the world best level at the signal/noise ratio, and minium illumination, power consumption part. The HD level triple streaming hybrid security camera in this paper will be widely used at the security camera because of the better performance and function.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.833-836
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• 2017

최근 블랙박스 및 CCTV 같은 영상 촬영 장치가 보편화되면서, 방대한 양의 영상 데이터가 실시간으로 생성되고 있다. 만약 이 대용량 데이터 안의 차량 정보를 추출할 수 있다면 범죄 차량 추적, 교통 혼잡도 측정 등의 활용이 가능할 것이다. 이를 구현하기 위해서는 수많은 자동차에서 실시간으로 생성되는 영상 데이터를 처리할 수 있는 시스템이 필수적이나, 이러한 시스템을 찾기 힘든 것이 현실이다. 이를 위해 이 논문에서는 아파치 카프카, Hbase를 이용한 영상 빅데이터 처리 시스템을 제안한다. 아파치 카프카는 시스템 내에서 영상 손실이 없는 전송과 영상 처리 노드의 스케줄링을 수행하며, Hbase는 처리된 데이터를 테이블로 저장하고 사용자가 보낸 쿼리를 처리한다. 더불어, Hbase에 인덱스를 구성하여 빠른 쿼리 처리가 가능하도록 만든다. 실험 결과, 제안된 시스템은 인덱스가 없을 때보다 뛰어난 쿼리 처리 성능을 보이는 것을 확인할 수 있었다.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.5
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• pp.472-477
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• 2016

The most important and critical to the performance of video surveillance systems is to be detected exactly how much. In order to accurately track the object must be able to accurately separate the background and object. However, the system itself rather than the human vision exactly distinguish the object and the background, to assess the situation, it is not easy. If we can accurately detect the background and the object, to be able to accurately track an object, it is possible to increase the reliability of the system, have a significant impact on the success of the entire production system. In this paper, we propose a way to distinguish more precisely the background and the object being to determine the background environment changes more accurately.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.3
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• pp.66-73
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• 2013

This study assesses neck injury of occupants in a real traffic accident case that a preceding vehicle moved backward and impacted a parked vehicle at a low velocity. This case is different from a case of whiplash injury caused by rear impact on vehicle. The impact velocity was estimated from damages of the two vehicle bumpers and the displacement of the parked vehicle was also estimated from CCTV images. MADYMO simulation was performed based on the vehicle specifications and investigation report. The comparison of neck flexion moments with the corresponding injury criteria revealed that occupants of the parked vehicle might have hardly neck injury.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.4
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• pp.237-245
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• 2017

This paper presents a fire detection algorithm using color and motion models from video sequences. The proposed method detects change in color and motion of overall regions for detecting fire, and thus, it can be implemented in both fixed and pan/tilt/zoom (PTZ) cameras. The proposed algorithm consists of three parts. The first part exploits color models of flames and smoke. The candidate regions in the video frames are extracted with the hue-saturation-value (HSV) color model. The second part models the motion information of flames and smoke. Optical flow in the fire candidate region is estimated, and the spatial-temporal distribution of optical flow vectors is analyzed. The final part accumulates the probability of fire in successive video frames, which reduces false-positive errors when fire-like color objects appear. Experimental results from 100 fire videos are shown, where various types of smoke and flames appear in indoor and outdoor environments. According to the experiments and the comparison, the proposed fire detection algorithm works well in various situations, and outperforms the conventional algorithms.