• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.466-468
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• 2022

3D reconstruction is important issue in many applications such as Augmented Reality (AR), eXtended Reality (XR), and Metaverse. For 3D reconstruction, depth map can be acquired by stereo camera and time-of-flight (ToF) sensor. We used both sensors complementarily to improve the accuracy of 3D information of the data. First, we applied general multi-camera calibration technique which uses both color and depth information. Next, the depth map of the two sensors are fused by 3D registration and reprojection approach. The fused data is compared with the ground truth data which is reconstructed using RTC360 sensor. We used Geomagic Wrap to analysis the average RMSE of the two data. The proposed procedure was implemented and tested with real-world data.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.4
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• pp.287-293
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• 2018

It is prerequisite to generate epipolar resampled images by reducing the y-parallax for accurate and efficient processing of satellite stereo images. Minimizing y-parallax requires the accurate sensor modeling that is carried out with ground control points. However, the approach is not feasible over inaccessible areas where control points cannot be easily acquired. For the case, a relative orientation can be utilized only with conjugate points, but its accuracy for satellite sensor should be studied because the sensor has different geometry compared to well-known frame type cameras. Therefore, we carried out the bias-compensation of RPCs (Rational Polynomial Coefficients) without any ground control points to study its precision and effects on the y-parallax in epipolar resampled images. The conjugate points were generated with stereo image matching with outlier removals. RPCs compensation was performed based on the affine and polynomial models. We analyzed the reprojection error of the compensated RPCs and the y-parallax in the resampled images. Experimental result showed one-pixel level of y-parallax for Kompsat-3 stereo data.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.3
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• pp.240-247
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• 2013

This paper proposes an optimal three-dimensional coordinate implementation of the vision sensor using two CCD cameras. The PBVS (Position based visual servoing) is implemented using the positional information obtained from images. Stereo vision by PBVS method that has enhanced every frame using calibration parameters is effective in the distance calculation. The IBVS (Image based visual servoing) is also implemented using the difference between reference and obtained images. Stereo vision by IBVS method calculates the distance using rotation angle of motors that correspond eyes and neck without enhanced images. The PBVS method is compared with the IBVS method in terms of advantages, disadvantages, computing time, and performances. Finally, the IBVS method is applied for the dual arm manipulator on the mobile inverted pendulum. The autonomous mobile inverted pendulum is successfully demonstrated using the center of the manipulator's mass.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.157-160
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• 2008

A realization for moving object detecting and tracking system in two dimensional plane using stereo line CCDs and lighting source is presented in this paper. Instead of processing camera images directly, two line CCD sensor and input line image is used to measure two dimensional distance by comparing the brightness on line CCDs. The algorithms are used the moving object tracking and coordinate converting method. To ensure the effective detection of moving path, a detection algorithm to evaluate the reliability of each measured distance is developed. The realized system results are that the performance of moving object recognizing shows 5mm resolution and mean error is 1.89%, and enables to track a moving path of object per 100ms period.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.173-177
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• 2002

This paper describes the algorithm for WMR (Wheeled Mobile Robot) to follow the preceding object using stereo vision. The center point of object existing in each image is calculate. From the distance and variation of two center points, we calculates the distance from WMR to preceding object and the relative velocity of WMR. And we use the Lyapunov theory to design controller.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.5
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• pp.315-322
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• 2019

DSM (Digital Surface Model) is a digital representation of ground surface topography or terrain that is widely used for hydrology, slope analysis, and urban planning. Aerial photogrammetry and LiDAR (Light Detection And Ranging) are main technology for urban DSM generation but high-resolution satellite imagery is the only ingredient for remote inaccessible areas. Traditional automated DSM generation method is based on correlation-based methods but recent study shows that a modern pixelwise image matching method, SGM (Semi-Global Matching) can be an alternative. Therefore this study investigated the application of SGM for Kompsat satellite data of KARI (Korea Aerospace Research Institute). Firstly, the sensor modeling was carried out for precise ground-to-image computation, followed by the epipolar image resampling for efficient stereo processing. Secondly, SGM was applied using different parameterizations. The generated DSM was evaluated with a reference DSM generated by the first pulse returns of the LIDAR reference dataset.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.3
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• pp.173-178
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• 2024

This study presents a technique for assessing the dimensional quality of assembly parts in Prefabricated Steel Structures (PSS) using a stereo vision sensor. The stereo vision system captures images and point cloud data of the assembly area, followed by applying image processing algorithms such as fuzzy-based edge detection and Hough transform-based circular bolt hole detection to identify bolt hole locations. The 3D center positions of each bolt hole are determined by correlating 3D real-world position information from depth images with the extracted bolt hole positions. Principal Component Analysis (PCA) is then employed to calculate coordinate axes for precise measurement of distances between bolt holes, even when the sensor and structure orientations differ. Bolt holes are sorted based on their 2D positions, and the distances between sorted bolt holes are calculated to assess the assembly part's dimensional quality. Comparison with actual drawing data confirms measurement accuracy with an absolute error of 1mm and a relative error within 4% based on median criteria.

• ETRI Journal
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• v.26 no.3
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• pp.218-228
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• 2004

Using stereo images with ephemeris data from the Korea Multi-Purpose Satellite-1 electro-optical camera (KOMPSAT-1 EOC), we performed geometric modeling for three-dimensional (3-D) positioning and evaluated its accuracy. In the geometric modeling procedures, we used ephemeris data included in the image header file to calculate the orbital parameters, sensor attitudes, and satellite position. An inconsistency between the time information of the ephemeris data and that of the center of the image frame was found, which caused a significant offset in satellite position. This time inconsistency was successfully adjusted. We modeled the actual satellite positions of the left and right images using only two ground control points and then achieved 3-D positioning using the KOMPSAT-1 EOC stereo images. The results show that the positioning accuracy was about 12-17 m root mean square error (RMSE) when 6.6 m resolution EOC stereo images were used along with the ephemeris data and only two ground control points (GCPs). If more accurate ephemeris data are provided in the near future, then a more accurate 3-D positioning will also be realized using only the EOC stereo images with ephemeris data and without the need for any GCPs.

• Korean Journal of Remote Sensing
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• v.21 no.3
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• pp.229-242
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• 2005

Photogrammetry is a current method of GIS data acquisition. However, as a matter of fact, a large manpower and expenditure for making detailed 3D spatial information is required especially in urban areas where various buildings exist. There are no photogrammetric systems which can automate a process of spatial information acquisition completely. On the other hand, LiDAR has high potential of automating 3D spatial data acquisition because it can directly measure 3D coordinates of objects, but it is rather difficult to recognize the object with only LiDAR data, for its low resolution at this moment. With this background, we believe that it is very advantageous to integrate LiDAR data and stereo CCD images for more efficient and automated acquisition of the 3D spatial data with higher resolution. In this research, the automatic urban object recognition methodology was proposed by integrating ultra highresolution stereo images and LiDAR data. Moreover, a method to enable more reliable and detailed stereo matching method for CCD images was examined by using LiDAR data as an initial 3D data to determine the search range and to detect possibility of occlusions. Finally, intellectual DSMs, which were identified urban features with high resolution, were generated with high speed processing.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.6
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• pp.27-34
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• 2011

In this paper, we propose an active 3D shape acquisition method based on photometric stereo using camera and flash on a smartphone. Two smartphones are used as the master and slave, in which the slave projects illumination from different locations while the master captures the images and processes photometric stereo algorithm to reconstruct 3D shape. In order to reduce the error, the smartphone's camera is calibrated to overcome the effect of the lens distortion and nonlinear camera sensor response. We apply 5-point algorithm to estimate the pose between smartphone cameras and then estimate lighting direction vector to run the photometric stereo algorithm. Experimental result shows that the proposed system enables us to use smartphone as a 3D camera with low cost and high quality.