• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.3
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• pp.191-204
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• 2014

In recent years, multi-camera systems have been recognized as an affordable alternative for the collection of 3D spatial data from physical surfaces. The collected data can be applied for different mapping(e.g., mobile mapping and mapping inaccessible locations)or metrology applications (e.g., industrial, biomedical, and architectural). In order to fully exploit the potential accuracy of these systems and ensure successful manipulation of the involved cameras, a careful system calibration should be performed prior to the data collection procedure. The calibration of a multi-camera system is accomplished when the individual cameras are calibrated and the geometric relationships among the different system components are defined. In this paper, a new single-step approach is introduced for the calibration of a multi-camera system (i.e., individual camera calibration and estimation of the lever-arm and boresight angles among the system components). In this approach, one of the cameras is set as the reference camera and the system mounting parameters are defined relative to that reference camera. The proposed approach is easy to implement and computationally efficient. The major advantage of this method, when compared to available multi-camera system calibration approaches, is the flexibility of being applied for either directly or indirectly geo-referenced multi-camera systems. The feasibility of the proposed approach is verified through experimental results using real data collected by a newly-developed indirectly geo-referenced multi-camera system.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.328-335
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• 2022

With the advance of robot capabilities and functionalities, construction robots assisting construction workers have been increasingly deployed on construction sites to improve safety, efficiency and productivity. For close-proximity human-robot collaboration in construction sites, robots need to be aware of the context, especially construction worker's behavior, in real-time to avoid collision with workers. To recognize human behavior, most previous studies obtained 3D human poses using a single camera or an RGB-depth (RGB-D) camera. However, single-camera detection has limitations such as occlusions, detection failure, and sensor malfunction, and an RGB-D camera may suffer from interference from lighting conditions and surface material. To address these issues, this study proposes a novel method of 3D human pose estimation by extracting 2D location of each joint from multiple images captured at the same time from different viewpoints, fusing each joint's 2D locations, and estimating the 3D joint location. For higher accuracy, the probabilistic representation is used to extract the 2D location of the joints, considering each joint location extracted from images as a noisy partial observation. Then, this study estimates the 3D human pose by fusing the probabilistic 2D joint locations to maximize the likelihood. The proposed method was evaluated in both simulation and laboratory settings, and the results demonstrated the accuracy of estimation and the feasibility in practice. This study contributes to ensuring human safety in close-proximity human-robot collaboration by providing a novel method of 3D human pose estimation.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.855-856
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• 2008

In this paper, we studied the performance evaluation of a vehicular rear-view camera through quantifying the image quality based on several objective criteria from the ISO (International Organization for Standardization). In addition, various experimental environments are defined considering the conditions under which a rear-view camera may need to operate. The process for evaluating the performance of a rear-view camera is composed of five objective criteria: noise test, resolution test, OECF (opto-electronic conversion function) test, color characterization test, and pincushion and barrel distortion tests. The proposed image quality quantification method then expresses the results of each test as a single value, allowing easy evaluation.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.12
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• pp.1033-1041
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• 2003

A new visual tracking scheme is proposed for a mobile robot that tracks a moving object in 3D space in real time. Visual tracking is to control a mobile robot to keep a moving target at the center of input image at all time. We made it possible by simplifying the relationship between the 2D image frame captured by a single camera and the 3D workspace frame. To precisely calculate the input vector (orientation and distance) of the mobile robot, the speed vector of the target is determined by eliminating the speed component caused by the camera motion from the speed vector appeared in the input image. The problem of temporary disappearance of the target form the input image is solved by selecting the searching area based on the linear prediction of target motion. The experimental results have shown that the proposed scheme can make a mobile robot successfully follow a moving target in real time.

• Journal of the Korean Society of Safety
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• v.30 no.6
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• pp.110-116
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• 2015

A 3D camera-based on-site work-related musculoskeletal disorder risk assessment(WMDs) tool has been developed. The device consists of Kinect a 3D camera manufactured by Microsoft, a servo-motor, and a mobile robot. To complement inherent narrow field of view(FOV) of Kinect, Kinect is rotated according to PID servo-control algorithm by a servo-motor attached underneath, to track movement of a subject, producing skeleton-based motion data. With servo-control, full 360 degrees tracking of a test subject is possible by single Kinect. It was found from experimental tests that the proposed device can be successfully employed for on-site WMDs risk assessing tool.

• The Journal of Korea Robotics Society
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• v.13 no.4
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• pp.237-247
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• 2018

In this paper, we describe a sensor module that monitors fire environment by analyzing fire characteristics. We analyzed the smoke characteristics of indoor fire. Six different environments were defined according to the type of smoke and the flame, and the sensors available for each environment were combined. Based on this analysis, the sensors were selected from the perspective of firefighter. The sensor module consists of an RGB camera, an infrared camera and a radar. It is designed with minimum weight to fit on the robot. the enclosure of sensor is designed to protect against the radiant heat of the fire scene. We propose a single camera mode, thermal stereo mode, data fusion mode, and radar mode that can be used depending on the fire scene. Thermal stereo was effectively refined using an image segmentation algorithm, SLIC (Simple Linear Iterative Clustering). In order to reproduce the fire scene, three fire test environments were built and each sensor was verified.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.543-547
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• 2002

In this paper, we introduce a more improved camera modeling method for linear pushbroom images than the method proposed by Orun and Natarajan(ON). ON model shows an accuracy of within 1 pixel if more than 10 ground control points(GCPs) are provided. In general, there is high correlation between platform position and attitude parameters but ON model ignores attitude variation in order to overcome such correlation. We propose a new method that obtains an optimal solution set of parameters without ignoring the attitude variation. We first assume that attitude parameters are constant and estimate platform position's. Then we estimate platform attitude parameters using the values of estimated position parameters. As a result, we can set up an accurate camera model for a linear pushbroom satellite scene. In particular, we can apply the camera model to its surrounding scenes because our model provide sufficient information on satellite's position and attitude not only for a single scene but also for a whole imaging segment. We tested on two images: one with a pixel size 6.6m$\times$6.6m acquired from EOC(Electro Optical Camera), and the other with a pixel size 10m$\times$l0m acquired from SPOT. Our camera model procedures were applied to the images and gave satisfying results. We had obtained the root mean square errors of 0.5 pixel and 0.3 pixel with 25 GCPs and 23 GCPs, respectively.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.11a
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• pp.143-152
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• 2004

Researchers seeking geological and environmental information, depend on remote sensing and aerial photographic datum from various commercial satellites and aircraft. However, adverse weather conditions as well as equipment expense limit the ability to collect data anywhere and anytime. To allow for better flexibility in geological and environmental data collection, we have developed a compact, multi-spectral automatic Aerial Photographic system (PKNU2). This system's Multi-spectral camera can record visible (RGB) and infrared (NIR) band (3032＊2008 Pixels) images Visible and infrared band images were obtained from each camera respectively and produced color-infrared composite images to be analyzed for the purpose of the environmental monitoring. However this did not provide quality data. Furthermore, it has the disadvantage of having the stereoscopic overlap area being 60% unsatisfied due to the 12 seconds of storage time of each data The PKNU2 system in contrast, photographed photos of great capacity Thus, with such results, we have been proceeding to develop the advanced PKNU2 (PKNU3) system that consists of a color-infrared spectral camera that can photograph in the visible and near-infrared bands simultaneously using a single sensor, a thermal infrared camera, two 40G computers to store images, and an MPEG board that can compress and transfer data to the computer in real time as well as be able to be mounted onto a helicopter platform.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.93-97
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• 2022

Infrared scenes usually contain also spectral information which cannot be resolved using normal single-band infrared cameras. Multispectral infrared imaging cameras give access to the comprehensive information contained within infrared scenes. A Dual-band infrared Camera, a type of multispectral infrared imaging cameras, has the advantage of simple system. A Dual-band Infrared Camera gives access to the spectral information as wells as the temperature information within infrared scenes. Multispectral imaging generally increases the detection and identification performance of a Dual-band Infrared Camera. This paper describes a design of an infrared Camera using a Dual-band Infrared Detector to simultaneously receive infrared radiation from the medium-wave infrared/long-wave infrared(MWIR/LWIR) bands.

• Journal of Korea Multimedia Society
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• v.16 no.2
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• pp.213-225
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• 2013

This paper proposes a design method of ball-plate robot controller using single camera and two motors to balance the ball on plate and reduce steady state control error. To design the ball-plate system, it is necessary to observe state of the ball and maintain balance of the plate. The state of the ball is tracked by using the CAMShift algorithm and position error of the ball is compensated by the Kalman filter. Balance of the plate is controlled by driving two motors and we used DC motors which has smaller measurement error. Due to surface condition of the plate or tracking error of ball's position, there are small errors remained. These errors are accumulated and disturb maintaining balance of the ball. To handle the problem, we propose a controller supplemented with an integrator.