• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.4
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• pp.295-303
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• 2018

The stereo camera system has a fixed baseline and therefore has a constant scale. However, it is difficult to measure the actual three-dimensional coordinate since the scale is not fixed when relative orientation parameters are determined through the key-point matching in the stereo image each time. Therefore, the purpose of this study was to perform the stereo camera calibration that simultaneously determines the internal characteristics of the left and right cameras and the camera relationship between them using the modified collinearity equation and compared it with the two independent single cameras calibration. In the experiment using the images taken at close range, the RMSE (Root Mean Square Error) of ${\pm}0.014m$ was occurred when the three dimensional distances were compared in the single calibration results. On the other hand, the accuracy of the three-dimensional distance of the stereo camera calibration was better because the stereo camera results were almost no error compared to the results from two single cameras. In the comparison of the epipolar images, the RMSE of the stereo camera was 0.3 pixel more than that of the two single cameras, but the effect was not significant.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.10a
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• pp.129-134
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• 2003

Mobile Mapping System needs system calibration of multi sensors. System calibration is defined as determination of spatial and rotational offsets between the sensors. Especially, EO parameters of GPS/INS require knowledge of the calibration to camera frame. The calibration parameters must be determined with the highest achievable accuracy in order to get 3D coordinate points in stereo CCD images. This study applies Boresight calibration for the calibration between GPS/INS and camera, and estimates the Performance of the calibration.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.279-284
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• 2004

This paper presents on adjustment methods of the vendor-provided RPC(Rational Polynomial Coefficient) of GEO-level stereo images for the IKONOS satellite. RPC are adjusted with control points by the first-order polynomial and the block adjustment method in this study. As results, the maximum error of 3D ground coordinates by the adjusted RPC model did not exceed 4m. The block adjustment method is more stability than the first-order polynomial method.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.04a
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• pp.245-248
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• 2003

본 연구에서는 수치영상처리 방법으로 공간해상도가 l0m인 SPOT 흑백영상을 사용하여, 지상기준점 수량을 10∼30개까지 5개 단위로 증가시키면서 각각의 모델링과 수치표고모델, 정사영상을 생성하여 정사영상상에서 정확도를 평가하였다.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.11a
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• pp.291-294
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• 2004

최근 들어 위성영상의 사용성 증대와 더불어 고정밀한 공간지리정보의 획득에 대한 관심이 증대되고 있으며, 모델링의 정확도 수준은 수치표고모형, 정사영상 등에 영향을 미치므로 고정밀 모델링 기법을 수행하여야함. 또한 비접근 지역의 경우 많은 기준점을 획득하기 어려우므로 최소 기준점 즉, 2점 의 GPS관측성과와 수치지도를 이용하여 궤도모델링을 수행한 후 모델링(Bundle Adj.)을 수행

• Journal of IKEEE
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• v.17 no.4
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• pp.517-524
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• 2013

Stereo matching has been grabbing the attention of researchers because it plays an important role in computer vision, remote sensing and photogrammetry. Although most methods perform well with small size images, experiments applying them to large-scale data sets under uncontrolled conditions are still lacking. In this paper, we present an empirical study on stereo matching for large-scale high-resolution satellite images. A new method is studied to solve the problem of huge size and memory requirement when dealing with large-scale high resolution satellite images. Integrating the tiling technique with the well-known dynamic programming and coarse-to-fine pyramid scheme as well as using memory wisely, the suggested method can be utilized for huge stereo satellite images. Analyzing 350 points from an image of size of 8192 x 8192, disparity results attain an acceptable accuracy with RMS error of 0.5459. Taking the trade-off between computational aspect and accuracy, our method gives an efficient stereo matching for huge satellite image files.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.04a
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• pp.151-159
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• 2003

This study presents method for self-calibration of the SEM(Scanning Electron Microscope) stereo image using the standard microprobe with same grid pattern and using parallel and central perspective projection equation. Result showed that parallel projection method is more suitable for standard microprobe. The maximum error of 3D coordinates acquired by this method did not exceed 5 $\mu\textrm{m}$, and DSM(Digital Surface Model) for three dimensional measurement of the rock sample was generated by the digital photogrammetry. This result can be used for quantification of micro scale change of shape and analysis of the micro morphology of rock due to weathering.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.19 no.1
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• pp.77-83
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• 2001

To product the map by terrestrial photogrammetry method, a few rather nuisance stereo image acquiring processing and plot using expensive analytical instruments have to be performed. In this study, plot was made by acquiring and rectification image using simple method rather than above it. For this, geometry rectification system was constructed for the generation of single ortho-image analysis. and these ortho-images of architecture were made and analysed by appling various warping methods. As a result, the performance of single image analysis could be estimated, and it is expected that the application of this is possible to various non-topographic photogrammetry.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.4
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• pp.399-404
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• 2002

In this study, it was intended to present solution for learners to understand and utilize photogrammetry more easily using economic medium except expensive measuring equipment. For this, 3D point data was analysed by generating event to stereo image on monitor, and input to CAD system automatically. so, real time vector editing and drawing with coordinates measurement were possible. The system was verified, and the monitoring for real construction was performed. so, it is expected to be utilized as a practical use software in related fields.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.2
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• pp.75-80
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• 2017

Recently, there has been growing interest in spatial data that combines information and communication technology with smart cities. The high-precision LiDAR (Light Dectection and Ranging) equipment is mainly used to collect three-dimensional spatial data, and the acquired data is also used to model geographic features and to manage plant construction and cultural heritages which require precision. The LiDAR equipment can collect precise data, but also has limitations because they are expensive and take long time to collect data. On the other hand, in the field of computer vision, research is being conducted on the methods of acquiring image data and performing 3D reconstruction based on image data without expensive equipment. Thus, precise 3D spatial data can be constructed efficiently by collecting and processing image data using CCTVs which are installed as infrastructure facilities in smart cities. However, this method can have an accuracy problem compared to the existing equipment. In this study, experiments were conducted and the results were analyzed to increase the number of extracted matching points by applying the feature-based method and the area-based method in order to improve the precision of 3D spatial data built with image data acquired from stereo CCTVs. For techniques to extract matching points, SIFT algorithm and PATCH algorithm were used. If precise 3D reconstruction is possible using the image data from stereo CCTVs, it will be possible to collect 3D spatial data with low-cost equipment and to collect and build data in real time because image data can be easily acquired through the Web from smart-phones and drones.