• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.1
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• pp.1-7
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• 2012

This paper presents a method for 3D image construction using the hybrid (color and depth) camera system, in which the drawbacks of each camera can be compensated for. Prior to an image generation, intrinsic parameters and extrinsic parameters of each camera are extracted through experiments. The geometry between two cameras is established with theses parameters so as to match the color and depth images. After the preprocessing step, the relation between depth information and distance is derived experimentally as a simple linear function, and 3D image is constructed by coordinate transformations of the matched images. The present scheme has been realized using the Microsoft hybrid camera system named Kinect, and experimental results of 3D image and the distance measurements are given to evaluate the method.

• Journal of Biosystems Engineering
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• v.24 no.1
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• pp.41-50
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• 1999

This study aims at detecting the three dimensional gripping points for the transplanting robot system to grip in the process of developing transplanting robot system, which is one of the automation systems for transplanting tissue culture. The stereo vision system equipped with two cameras has been used to detect the gripping points of the plant stem. The method for matching the plants of the image information which came from two cameras was to measure the total numbers of pixels, leaves, and the heights of the plants. The gripping points were detected near the roots after extracting the stem parts by the standard deviation of the X axis according to the Y axis. The performance test of the developed program showed that the detecting errors of the gripping points were 0∼1mm for X axis and 1∼2mm for Y & Z axis. The mean running time of the program was about 3 seconds.

• 한국가시화정보학회:학술대회논문집
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• 2003.11a
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• pp.39-42
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• 2003

Leading edge extension(LEX) in a highly swept shape applied to a delta wing features the modern air-fighters. The LEX vortices generated upon the upper surface of the wing at high angle of attack enhance the lift force of the delta wing by way of increased negative suction pressure over the surfaces. The present 3-D stereo PIV includes the Identification of 2-D cross-correlation equation, stereo matching of 2-D velocity vectors of two cameras, accurate calculation of 3-D velocity vectors by homogeneous coordinate system, removal of error vectors by a statistical method followed by a continuity equation criterion and so on. A delta wing model with or without LEX was immersed in a circulating water channel. Two high-resolution, high-speed digital cameras$(1280pixel\times1024pixel)$ were used to allow the time-resolved animation work. The present dynamic stereo PIV represents the complicated vortex behavior, especially, in terms of time-dependent characteristics of the vortices at given measuring sections. Quantities such as three velocity vector components, vorticity and other flow information can be easily visualized via the 3D time-resolved post-processing to make the easy understanding of the LEX effect or vortex emerging and collapse which are important phenomena occurring in the field of delta wing aerodynamics.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.3
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• pp.123-132
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• 2021

To determine 3D(three-dimensional) positions using a stereo-camera in close-range photogrammetry, camera calibration to determine not only the interior orientation parameters of each camera but also the relative orientation parameters between the cameras must be preceded. As time passes after performing camera calibration, in the case of non-metric cameras, the interior and relative orientation parameters may change due to internal instability or external factors. In this study, to evaluate the stability of the stereo-camera, not only the stability of two single cameras and a stereo-camera were analyzed, but also the three-dimensional position accuracy was evaluated using checkpoints. As a result of evaluating the stability of two single cameras through three camera calibration experiments over four months, the root mean square error was ±0.001mm, and the root mean square error of the stereo-camera was ±0.012mm ~ ±0.025mm, respectively. In addition, as the results of distance accuracy using the checkpoint were ±1mm, the interior and relative orientation parameters of the stereo-camera were considered stable over that period.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.6
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• pp.611-616
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• 2008

When extracting geo-referenced 3D data from cameras mounted on Mobile Mapping Systems, one of important properties for accuracy of extracted data is the alignment of the relative translation(lever-arm) and rotation(bore-sight) between the coordinate systems of Inertial Measurement Unit(IMU)/Ground Positioning System(GPS) and cameras. Since the conventional method calculates absolute camera orientation using ground control points (GCP), the alignment is determined in one Coordinated System (GPS Coordinated System). It basically require GCP. We proposed a mathematical model for the alignment using the initially uncoupled data of cameras and IMU/GPS without GCPs.

• Journal of Sensor Science and Technology
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• v.8 no.1
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• pp.80-88
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• 1999

This paper deals with the position determination problem of stereo camera systems used as a sensor for 3D robotic manipulation. Stereo cameras having parallel rays of sight and been set up on the same baseline are assumed. The distance between the sensor and the space measured is determined so as to get insensitive parameters to the uncertainty of control points used for calibration and to satisfy the error condition set by considering the repeatability of the robot. The baseline width is determined by minimizing the mutual effect of 3D positional error and stereo image coordinate error. Unlike existing techniques, the technique proposed here is developed without complicated constraints and modelling process of the object to be observed. Thus, the technique of this paper is more general and its effectiveness is proved by simulation.

• Journal of Advanced Marine Engineering and Technology
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• v.23 no.2
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• pp.259-269
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• 1999

A new algorithm for measuring 3-D velocity components of high speed flows were developed using a digital image processing technique. The measuring system consists of three CCD cameras an optical instrument called AOM a digital image grabber and a host computer. The images of mov-ing particles arranged spatially on a rotation plate are taken by two or three CCD cameras and are recorderd onto the image grabber or a video tape recoder. The three-dimensionl velocity com-ponents of the particles are automatically obtained by the developed algorithm In order to verify the validity of this technique three-dimensional velocity data sets obtained from a computer simu-lation of a backward facing step flow were used as test data for the algorithm. an uncertainty analysis associated with the present algorithm is systematically evaluated, The present technique is proved to be used as a tookl for the measurement of unsteady three-dimensional fluid flows.

• Smart Media Journal
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• v.11 no.9
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• pp.75-80
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• 2022

Recently, research and development on immersive virtual reality(VR) technology to provide a realistic experience is being widely conducted. To provide realistic experience in immersive virtual reality for VR participants, virtual environments should consist of high-realistic environments using 3D reconstruction. In this paper, to acquire 3D information in real space using multiple cameras in the reconstruction process, we propose a novel method of optimal camera placement for accurate reconstruction to minimize distortion of 3D information. Through our approach in this paper, real 3D information can obtain with minimized errors during environment reconstruction, and it is possible to provide a more immersive experience with the created virtual environment.

• Journal of Multimedia Information System
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• v.9 no.3
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• pp.183-190
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• 2022

Image-based 3D object detection is one of the important and difficult problems in autonomous driving and robotics, and aims to find and represent the location, dimension and orientation of the object of interest. It generates three dimensional (3D) bounding boxes with only 2D images obtained from cameras, so there is no need for devices that provide accurate depth information such as LiDAR or Radar. Image-based methods can be divided into three main categories: monocular, stereo, and multi-view 3D object detection. In this paper, we investigate the recent state-of-the-art models of the above three categories. In the multi-view 3D object detection, which appeared together with the release of the new benchmark datasets, NuScenes and Waymo, we discuss the differences from the existing monocular and stereo methods. Also, we analyze their performance and discuss the advantages and disadvantages of them. Finally, we conclude the remaining challenges and a future direction in this field.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.2054-2059
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• 2003

3D-PTV measurement was conducted on the wake of a goldfish in order to understand its swimming motions. The measurement system consisted of three CCD cameras, an image grabber, an Ar-Ion laser and a host computer. The flow properties of the wake of the goldfish were measured under three different velocities of the currents. Unsteady flow structures around the goldfish were quantitatively clarified using the time-consecutive instantaneous three-dimensional vectors obtained by the constructed 3D-PTV system.