• 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.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.484-486
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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 falloff from train platforms. Recently, advancements in IT have enabled applying vision sensors to railway environments, such as CCTV and stereo camera sensors. In this paper, we propose a stereoscopic video coding scheme for subway accident monitoring system. The proposed scheme is designed for providing flexible video among various displays, such as control center, station employees and train driver. We uses MPEG-2 standard for coding the left-view sequence and IBMDC for predicting the P- and B-types of frames of the right-view sequence. IBMDC predicts matching block by interpolating both motion and disparity predicted macroblocks. To provide efficient stereoscopic video service. we define both temporally and spatially scalable layers for each eye's-view by using the concept of Spatio-Temporal scalability. According to the experimental results. we expect the proposed functionalities will play a key role in establishing highly flexible stereoscopic video codec for ubiquitous display environment where devices and network connections are heterogeneous.

• Journal of the Korea Computer Graphics Society
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• v.16 no.1
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• pp.1-7
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• 2010

With the widespread use of vision-based surveillance systems, the capability for person identification is now an essential component. However, the CCTV cameras used in surveillance systems tend to produce relatively low-resolution images, making it difficult to use face recognition techniques for person identification. Therefore, an algorithm is proposed for person identification in CCTV camera images based on the clothing. Whenever a person is authenticated at the main entrance of a building, the clothing feature of that person is extracted and added to the database. Using a given image, the clothing area is detected using background subtraction and skin color detection techniques. The clothing feature vector is then composed of textural and color features of the clothing region, where the textural feature is extracted based on a local edge histogram, while the color feature is extracted using octree-based quantization of a color map. When given a query image, the person can then be identified by finding the most similar clothing feature from the database, where the Euclidean distance is used as the similarity measure. Experimental results show an 80% success rate for person identification with the proposed algorithm, and only a 43% success rate when using face recognition.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.12
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• pp.2355-2362
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• 2016

Seg fog removal is an important issue concerned by both computer vision and image processing. Sea fog or haze removal is widely used in lots of fields, such as automatic control system, CCTV, and image recognition. Color image dehazing techniques have been extensively studied, and expecially the dark channel prior(DCP) technique has been widely used. This paper propose a fast and efficient image prior - dark channel prior to remove seg-fog from a single digital image based on the GPU. We implement the basic parallel program and then optimize it to obtain performance acceleration with more than 250 times. While paralleling and the optimizing the algorithm, we improve some parts of the original serial program or basic parallel program according to the characteristics of several steps. The proposed GPU programming algorithm and implementation results may be used with advantages as pre-processing in many systems, such as safe navigation for ship, topographical survey, intelligent vehicles, etc.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.4
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• pp.641-647
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• 2018

Recently, CCTV, which provides video information for multiple purposes, has been transformed into an intelligent, and the range of automation applications increased using the computer vision. A highly reliable detection method must be performed for accurate recognition of pedestrians and vehicles and various methods are being studied for this purpose. In such an object detection system. In this paper, we propose a method to detect a large number of pedestrians by acquiring three characteristic information that features of color information using HSI, motion vector information and shaping information using HOG feature information of a pedestrian in a situation where a large number of pedestrians are moving. The proposed method distinguishes each pedestrian while minimizing the failure or confusion of pedestrian detection and tracking. Also when pedestrians approach or overlap, pedestrians are identified and detected using stored frame feature data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.5
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• pp.668-674
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• 2022

Machine learning techniques using visual data have high usability in fields of industry and service such as scene recognition, fault detection, security and user analysis. Among these, user analysis through the videos from CCTV is one of the practical way of using vision data. Also, many studies about lightweight artificial neural network have been published to increase high usability for mobile and embedded environment so far. In this study, we propose the network combining the object detection and classification for mobile graphic processing unit. This network detects pedestrian and face, classifies age and gender from detected face. Proposed network is constructed based on MobileNet, YOLOv2 and skip connection. Both detection and classification models are trained individually and combined as 2-stage structure. Also, attention mechanism is used to improve detection and classification ability. Nvidia Jetson Nano is used to run and evaluate the proposed system.

• Proceedings of the Korean Geotechical Society Conference
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• 2009.09a
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• pp.117-129
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• 2009

This paper studied the safety management network system of infrastructure which constructed smart sensors, closed-circuit television(CCTV) and monitoring system. This safety management of infrastructure applied to bridge, cut slop and tunnel, embankment etc. The system applied to technologies of standardization guidelines, data acquirement technologies, data analysis and judgment technologies, system integration setup technology, and IT technologies. It was constructed safety management network system of various infrastructure to improve efficient management and operation for many infrastructure. Integrated safety management network system of infrastructure consisted of the real-time structural health monitoring system of each infrastructure, integrated control center, measured data transmission using i of tet web-based, collecting data using sf ver, early alarm system which the dangerous event of infrastructure occurred. Integrated control center consisted of conference room, control room to manage and analysis the data, server room to present the measured data and to collect the raw data. Early alarm system proposed realization of warning and response within 5 minute or less through development of sensor-based progress report and propagation automation system using the media such as MMS, VMS, EMS, FMS, SMS and web services of report and propagation. Based on this, the most effective u-Infrastructure Safety Management System is expected to be stably established at a less cost, thus making people's life more comfortable. Information obtained from such systems could be useful for maintenance or structural safety evaluation of existing structures, rapid evaluation of conditions of damaged structures after an earthquake, estimation of residual life of structures, repair and retrofitting of structures, maintenance, management or rehabilitation of historical structures.

• Journal of Korea Multimedia Society
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• v.20 no.2
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• pp.196-204
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• 2017

Behavior of intelligent video surveillance system is recognized by analyzing the pattern of the object of interest by using the frame information of video inputted from the camera and analyzes the behavior. Detection of object's certain behaviors in the crowd has become a critical problem because in the event of terror strikes. Recognition of object's certain behaviors is an important but difficult problem in the area of computer vision. As the realization of big data utilizing machine learning, data mining techniques, the amount of video through the CCTV, Smart-phone and Drone's video has increased dramatically. In this paper, we propose a multiple-sliding window method to recognize the cumulative change as one piece in order to improve the accuracy of the recognition. The experimental results demonstrated the method was robust and efficient learning units in the classification of certain behaviors.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.2
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• pp.257-263
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• 2013

In case of image observation equipments, CCTV for short distance visual field is usually installed and operated mostly as the means of crime-prevention. However, the extensive demand for monitoring problems in case of the increase in intelligent crimes and disasters has led to the necessity of the development of long-distance observation equipments embedded with Night View functions. In case of the Night View equipments, the relevant market is set up to be focused mostly on Thermal Observation Device(hereinafter, TOD), but some shortcomings such as the limitation of image visibility and excessive maintenance cost, etc. have actually caused the necessity of new long distance Night View equipment. Moreover there might follow lots of difficulties in long-distance visualization in the event that irregular reflection is generated by minute particles in the atmosphere such as fog, smog, and dust, etc. These factors are motivate the work presented in this study. Our study is aimed at the realization of Pulsed Laser Illuminator and newly proposed Range-Gated image acquisition technology. And also the implementation of Tracker for continuous trace of the objects of interest from the obtained sequence images.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.7
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• pp.655-663
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• 2017

With the development of ICT technology, the indoor utilization of robots is increasing. Research on transportation, cleaning, guidance robots, etc., that can be used now or increase the scope of future use will be advanced. To facilitate the use of mobile robots in indoor spaces, the problem of self-location recognition is an important research area to be addressed. If an unexpected collision occurs during the motion of a mobile robot, the position of the mobile robot deviates from the initially planned navigation path. In this case, the mobile robot needs a robust controller that enables the mobile robot to accurately navigate toward the goal. This research tries to address the issues related to self-location of the mobile robot. A robust position recognition system was implemented; the system estimates the position of the mobile robot using a combination of encoder information of the mobile robot and the absolute space coordinate transformation information obtained from external video sources such as a large number of CCTVs installed in the room. Furthermore, vector field histogram method of the pass traveling algorithm of the mobile robot system was applied, and the results of the research were confirmed after conducting experiments.