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Evaluation of sequential images for photogrammetrically point determination

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Treść / Zawartość
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Close range photogrammetry encounters many problems with reconstruction of objects three-dimensional shape. Relative orientation parameters of taken photos makes usually key role leading to right solution of this problem. Automation of technology process is hardly performed due to recorded scene complexity and configuration of camera positions. This configuration makes the process of joining photos into one set usually impossible automatically. Application of camcorder is the solution widely proposed in literature for support in 3D models creation. Main advantages of this tool are connected with large number of recorded images and camera positions. Exterior orientation changes barely between two neighboring frames. Those features of film sequence gives possibilities for creating models with basic algorithms, working faster and more robust, than with remotely taken photos. The first part of this paper presents results of experiments determining interior orientation parameters of some sets of frames, presenting three-dimensional test field. This section describes calibration repeatability of film frames taken from camcorder. It is important due to stability of interior camera geometric parameters. Parametric model of systematical errors was applied for correcting images. Afterwards a short film of the same test field had been taken for determination of check points group. This part has been done for controlling purposes of camera application in measurement tasks. Finally there are presented some results of experiments which compare determination of recorded object points in 3D space. In common digital photogrammetry, where separate photos are used, first levels of image pyramids are taken to connect with feature based matching. This complicated process creates a lot of emergencies, which can produce false detections of image similarities. In case of digital film camera, authors of publications avoid this dangerous step, going straightly to area based matching, aiming high degree of similarity for two corresponding film frames. First approximation, in establishing connections between photos, comes from whole image distance. This image distance method can work with more than just two dimensions of translation vector. Scale and angles are also used for improving image matching. This operation creates more similar looking frames where corresponding characteristic points lays close to each other. Procedure searching for pairs of points works faster and more accurately, because analyzed areas can be reduced. Another proposed solution comes from image created by adding differences between particular frames, gives more rough results, but works much faster than standard matching.
Rocznik
Tom
Strony
285--296
Opis fizyczny
Bibliogr. 4 poz.
Twórcy
autor
  • Department of Photogrammetry Remote Sensing and Spatial Information Systems Faculty of Geodesy and Cartography, Warsaw University of Technology Pl. Politechniki 1, 00-661 Warszawa, Poland
Bibliografia
  • 1.Ding Y., Zhang J. Q., 2008, Architectural Scene Rapid Reconstruction Based on Features. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B3b. Beijing 2008.
  • 2.Fischler, M, A, Bolles, R, C, 1981: “Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography”, Commun. ACM, vol. 24, no. 6, pp. 381-395, June 1981.
  • 3.Gerke M., 2008, Dense Image Matching In Airborne Video Sequences. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B3b. Beijing 2008.
  • 4.Tian Y., Gerke M., Vosselman G., Zhu Q., 2008, Automatic Edge Matching Across an Image Sequence Based on Reliable Points The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B3b. Beijing 2008.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-4117e972-507a-44d7-94d0-7ea8dad3bc81
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