• Korean Journal of Computational Design and Engineering
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• v.20 no.4
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• pp.357-366
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• 2015

We review recent research results on coupled line cameras (CLC) as a new geometric tool to reconstruct a scene quadrilateral from image quadrilaterals. Coupled line cameras were first developed as a camera calibration tool based on geometric insight on the perspective projection of a scene rectangle to an image plane. Since CLC comprehensively describes the relevant projective structure in a single image with a set of simple algebraic equations, it is also useful as a geometric reconstruction tool, which is an important topic in 3D computer vision. In this paper we first introduce fundamentals of CLC with reals examples. Then, we cover the related works to optimize the initial solution, to extend for the general quadrilaterals, and to apply for cuboidal reconstruction.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.05b
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• pp.109-114
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• 2003

Depth error correction effect for maladjusted stereo cameras with calibrated pixel distance parameter is presented. The camera calibration is a necessary procedure for stereo vision-based depth computation. Intra and extra parameters should be obtain to determine the relation between image and world coordination through experiment. One difficulty is in camera alignment for parallel installation: placing two CCD arrays in a plane. No effective methods for such alignment have been presented before. Some amount of depth error caused from such non-parallel installation of cameras is inevitable. If the pixel distance parameter which is one of intra parameter is calibrated with known points, such error can be compensated in some amount. Such error compensation effect with the calibrated pixel distance parameter is demonstrated with various experimental results.

• Journal of Korea Multimedia Society
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• v.22 no.2
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• pp.128-135
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• 2019

This paper presents a deep learning-based object detection method for recognizing vehicles in images acquired through cameras installed on ceiling of underground parking lot. First, we present an image enhancement method, which improves vehicle detection performance under dark lighting environment. Second, we present a new CNN-based multiscale classifiers for detecting vehicles in images acquired through cameras with fisheye lens. Experiments show that the presented vehicle detector has better performance than the conventional ones.

• Journal of the Korea Society of Computer and Information
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• v.24 no.1
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• pp.107-113
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• 2019

Along with the development of IOT, the number of people using IOT devices has enormously increased and the IOT era has come. Especially, people using the IP cameras among Internet devices have been drastically increasing. It is because the IP cameras are well networked and comparatively cheap compared with CCTVs, and they can also be monitored and controlled in real time through PCs and smart phones for the purposes of general theft prevention and shop surveillance. However, due to the user's serious lack of security awareness and the fact that anyone can easily hack only with simple hacking tools and hacking sites information, security crimes that exploit those have been increasing as well. Therefore, this paper describes how easily the IP cameras can be hacked in the era of IOT, what kind of security incidents occurred, and also suggests possible government measures and new technical solutions to those problems.

• 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.

• Journal of IKEEE
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• v.20 no.2
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• pp.128-135
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• 2016

Smart care surveillance system provides the services to track users automatically by using the nearest CCTV cameras which are capable of monitoring them after the system searches for CCTV cameras around them by using the GPS location information received from them. Because users send their GPS location information with using their smart device when they are in emergency situation or want to be cared for, they may expect quick response of helper in this system. However, in the previous system, the selection time of camera which is capable of monitoring is increased rapidly as the management area is expended because the area management server selects the camera by sorting the distance between all of CCTV cameras and users, and then monitors them whenever they send the location information. In this paper, we propose the method to reduce the selection time of the CCTV cameras for tracking the users by searching only the cameras near to the CCTV cameras used to track them.

• Journal of the Korean Society for Nondestructive Testing
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• v.34 no.3
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• pp.248-253
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• 2014

Camera calibration is an indispensable process for improving measurement accuracy in industry fields such as machine vision. However, existing calibration cannot be applied to the calibration of mid-wave and long-wave infrared cameras. Recently, with the growing use of infrared thermal cameras that can measure defects from thermal properties, development of an applicable calibration target has become necessary. Thus, based on heat conduction analysis using finite element analysis, we developed a calibration target that can be used with both existing visible cameras and infrared thermal cameras, by implementing optimal design conditions, with consideration of factors such as thermal conductivity and emissivity, colors and materials. We performed comparative experiments on calibration target images from infrared thermal cameras and visible cameras. The results demonstrated the effectiveness of the proposed calibration target.

• Journal of KIISE
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• v.44 no.12
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• pp.1319-1332
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• 2017

In recent years, the number of video cameras that are used to record and broadcast live sporting events has increased, and selecting the shots with the best view from multiple cameras has been an actively researched topic. Existing approaches have assumed that the background in video is fixed. However, this paper proposes a best view selection method for cases in which the background is not fixed. In our study, an athlete of interest was recorded in video during motion with multiple cameras. Then, each frame from all cameras is analyzed for establishing rules to select the best view. The frames were selected using our system and are compared with what human viewers have indicated as being the most desirable. For the evaluation, we asked each of 20 non-specialists to pick the best and worst views. The set of the best views that were selected the most coincided with 54.5% of the frame selection using our proposed method. On the other hand, the set of views most selected as worst through human selection coincided with 9% of best view shots selected using our method, demonstrating the efficacy of our proposed method.

• International Journal of Aeronautical and Space Sciences
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• v.10 no.2
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• pp.86-94
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• 2009

This paper deals with the creation of a new, low-cost point/position tracking system that can measure deformations in engineering structures with simple commercially widespread cameras. Though point tracking systems do exist today, such as Stereo Pattern Recognition (SPR) and Projection Moir$\acute{e}$ Interferometry (PMI) systems, they are far too costly to use to analyze small, simple structures because complex optical components such as large flashes, high-resolution cameras and data acquisition systems with several computers are required. We developed a point tracking system using commercial cameras. This system used IR LEDs and commercial IR CCD cameras to minimize the interference posed by other extraneous light sources. The main algorithm used for this system is an optical point tracking algorithm, which is composed of the point extraction algorithm and the point matching algorithm for 3-D motion estimation. a series of verification tests were performed. Then, the developed point tracking system was applied to measure deformations of an acrylic plate under a mechanical load. The measured deformations of the acrylic plate matched well with the numerical analysis results. The results indicate that the developed point tracking system is reliable enough to measure continuous deformed shapes of various engineering structures.

• Journal of Biosystems Engineering
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• v.42 no.4
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• pp.330-338
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• 2017

Purpose: The smartphone is actively being used in many research fields, primarily in medical and diagnostic applications. However, there are cases in which smartphone-based systems have been developed for agriculture, environment, and food applications. The purpose of this review is to summarize the research cases using smartphone cameras in agriculture, environment, and food. Methods: This review introduces seventeen research cases which used smartphone cameras in agriculture, food, water, and soil applications. These were classified as systems involving "smartphone-camera-alone" and "smartphone camera with optical accessories". Results: Detecting food-borne pathogens, analyzing the quality of foods, monitoring water quality and safety, gathering information regarding plant growth or damage, identifying weeds, and measuring soil loss after rain were presented for the smartphone-camera-alone system. Measuring food and water quality and safety, phenotyping seeds, and soil classifications were presented for the smartphone camera with optical accessories. Conclusions: Smartphone cameras were applied in various areas for several purposes. The use of smartphone cameras has advantages regarding high-resolution imaging, manual or auto exposure and focus control, ease of use, portability, image storage, and most importantly, programmability. The studies discussed were achieved by sensitivity improvements of CCDs (charge-coupled devices) and CMOS (complementary metal-oxide-semiconductor) on smartphone cameras and improved computing power of the smartphone, respectively. A smartphone camera-based system can be used with ease, low cost, in near-real-time, and on-site. This review article presents the applications and potential of the smartphone and the smartphone camera used for various purposes in agriculture, environment, and food.