• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.2
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• pp.137-148
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• 2004

In this paper, we propose a new camera calibration method for rotating multi-view cameras to generate image-based panoramic 3D Virtual Environment. Since calibration accuracy worsens with an increase in distance between camera and calibration pattern, conventional camera calibration algorithms are not proper for panoramic 3D VE generation. To remedy the problem, a geometric relationship among all lenses of a multi-view camera is used for intra-camera calibration. Another geometric relationship among multiple cameras is used for inter-camera calibration. First camera parameters for all lenses of each multi-view camera we obtained by applying Tsai's algorithm. In intra-camera calibration, the extrinsic parameters are compensated by iteratively reducing discrepancy between estimated and actual distances. Estimated distances are calculated using extrinsic parameters for every lens. Inter-camera calibration arranges multiple cameras in a geometric relationship. It exploits Iterative Closet Point (ICP) algorithm using back-projected 3D point clouds. Finally, by repeatedly applying intra/inter-camera calibration to all lenses of rotating multi-view cameras, we can obtain improved extrinsic parameters at every rotated position for a middle-range distance. Consequently, the proposed method can be applied to stitching of 3D point cloud for panoramic 3D VE generation. Moreover, it may be adopted in various 3D AR applications.

• Journal of the Optical Society of Korea
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• v.5 no.2
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• pp.49-54
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• 2001

Research on shooting conditions of 3D program production for natural 3D images has been continued. In the study, it has been shown that orthostereoscopic conditions bring about no inconsistency between depth information from perspective of the lenses and that from binocular parallax. A newly developed 3D camera is based on orthostereoscopic conditions, which result in compactness of the camera (weight 8). At the same time, the new camera has a zooming function and is valuable in many ways, especially sport broadcasting. In this paper, we give an outline of the newly developed 3D HDTV camera and the results of subjective evaluation tests on psychological effects of the images shot by the camera. These tests show that the images shot by this camera are more powerful and comfortable to view than those shot by existing 3D cameras.

• Journal of Broadcast Engineering
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• v.24 no.2
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• pp.281-291
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• 2019

Depth from defocus estimates the 3D depth by using a phenomenon in which the object in the focal plane of the camera forms a clear image but the object away from the focal plane produces a blurred image. In this paper, algorithms are studied to estimate 3D depth by analyzing the degree of blur of the image taken with a single camera. The optimized object range was obtained by 3D depth estimation derived from depth from defocus using one image of a single camera or two images of different focus of a single camera. For depth estimation using one image, the best performance was achieved using a focal length of 250 mm for both smartphone and DSLR cameras. The depth estimation using two images showed the best 3D depth estimation range when the focal length was set to 150 mm and 250 mm for smartphone camera images and 200 mm and 300 mm for DSLR camera images.

• Proceedings of the KSME Conference
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• 2002.08a
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• pp.507-510
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• 2002

An algorithm of 3-D particle image velocimetry(3D-PIV) was developed for the measurement of 3-D velocity Held of complex flows. The measurement system consists of two or three CCD camera and one RGB image grabber. Flows size is $1500{\times}100{\times}180(mm)$, particle is Nylon12(1mm) and illuminator is Hollogen type lamp(100w). The stereo photogrammetry is adopted for the three dimensional geometrical mesurement of tracer particle. For the stereo-pair matching, the camera parameters should be decide in advance by a camera calibration. Camera parameter calculation equation is collinearity equation. In order to calculate the particle 3-D position based on the stereo photograrnrnetry, the eleven parameters of each camera should be obtained by the calibration of the camera. Epipolar line is used for stereo pair matching. The 3-D position of particle is calculated from the three camera parameters, centers of projection of the three cameras, and photographic coordinates of a particle, which is based on the collinear condition. To find velocity vector used 3-D position data of the first frame and the second frame. To extract error vector applied continuity equation. This study developed of various 3D-PIV animation technique.

• Journal of Sensor Science and Technology
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• v.23 no.1
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• pp.66-71
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• 2014

Vision is the most important sensing capability for both men and sensory smart machines, such as intelligent robots. Sensed real 3D world and its 2D camera image can be related mathematically by a process called camera calibration. In this paper, we present a novel linear solution of camera calibration. Unlike most existing linear calibration methods, the proposed technique of this paper can identify camera parameters explicitly. Through the step-by-step procedure of the proposed method, the real physical elements of the perspective projection transformation matrix between 3D points and the corresponding 2D image points can be identified. This explicit solution will be useful for many practical 3D sensing applications including robotics. We verified the proposed method by using various cameras of different conditions.

• Journal of Sensor Science and Technology
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• v.22 no.6
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• pp.387-392
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• 2013

Camera rigs for shooting 3D video are classified as manual, motorized, or fully automatic. Even in an automatic camera rig, the process of Stereoscopic 3D (S3D) video capture is very complex and time-consuming. One of the key time-consuming operations is capturing the distance parameters, which are near distance, far distance, and convergence distance. Traditionally these distances are measured by tape measure or triangular indirect measurement methods. These two methods consume a long time for every scene in shot. In our study, a compact laser distance sensing system with long range distance sensitivity is developed. The system is small enough to be installed on top of a camera and the measuring accuracy is within 2% even at a range of 50 m. The shooting time of an automatic camera rig equipped with the laser distance sensing system can be reduced significantly to less than a minute.

• Journal of Broadcast Engineering
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• v.24 no.5
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• pp.765-774
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• 2019

In this paper, we propose a point cloud matching algorithm for multiple RGB-D cameras. In general, computer vision is concerned with the problem of precisely estimating camera position. Existing 3D model generation methods require a large number of cameras or expensive 3D cameras. In addition, the conventional method of obtaining the camera external parameters through the two-dimensional image has a large estimation error. In this paper, we propose a method to obtain coordinate transformation parameters with an error within a valid range by using depth image and function optimization method to generate omni-directional three-dimensional model using 8 low-cost RGB-D cameras.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.3
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• pp.27-33
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• 2003

The image-based 3D modeling is the technique of generating a 3D graphic model from images acquired using cameras. It is being researched as an alternative technique for the expensive 3D scanner. In this paper, we propose the image-based, 3D modeling system using calibrated stereo cameras. The proposed algorithm for rendering, 3D model consists of three steps, camera calibration, 3D reconstruction, and 3D registration step. In the camera calibration step, we estimate the camera matrix for the image aquisition camera. In the 3D reconstruction step, we calculate 3D coordinates using triangulation from corresponding points of the stereo image. In the 3D registration step, we estimate the transformation matrix that transforms individually reconstructed 3D coordinates to the reference coordinate to render the single 3D model. As shown the result, we generated relatively accurate 3D model.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.911-912
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• 2013

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.1
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• pp.127-135
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• 2006

The image-based 3D modeling is the technique of generating a 3D graphic model from images acquired using cameras. It is being researched as an alternative technique for the expensive 3D scanner. In this paper, I propose the image-based 3D modeling system using calibrated camera. The proposed algorithm for rendering 3D model is consisted of three steps, camera calibration, 3D shape reconstruction and 3D surface generation step. In the camera calibration step, I estimate the camera matrix for the image aquisition camera. In the 3D shape reconstruction step, I calculate 3D volume data from silhouette using pyramidal volume intersection. In the 3D surface generation step, the reconstructed volume data is converted to 3D mesh surface. As shown the result, I generated relatively accurate 3D model.