Wieloobrazowe dopasowanie zdjęć bliskiego zasięgu do automatycznej rekonstrukcji fotorealistycznych modeli 3D

• Autorzy: Zawieska D.

Warianty tytułu

EN

Multi-image matching of close range photographs for photorealistic 3D models reconstruction

• Języki publikacji: PL

Abstrakty

PL

Modelowanie obiektu, wykorzystujące obrazy cyfrowe, zostało zdefiniowane jako kompletny proces rozpoczynający się pozyskaniem obrazów, a kończący utworzeniem interaktywnego, wirtualnego modelu 3D. Teza, jaką przyjęto w niniejszej rozprawie, opiera się na założeniu, że przez dobór odpowiednich algorytmów przetwarzania obrazów cyfrowych, wykorzystywanych w środowisku fotogrametrycznym i widzeniu maszynowym (CV), umożliwia wieloobrazowe, automatyczne dopasowanie obrazów cyfrowych bliskiego zasięgu, w celu wykonania automatycznej rekonstrukcji foto realistycznych modeli 3D wybranych obiektów. Na podstawie przeglądu literatury krajowej i zagranicznej przeprowadzono analizę rozwiązań istniejących systemów pomiarowych, wykorzystywanych do modelowania 3D w fotogrametrii bliskiego zasięgu. W analizie uwzględniono takie czynniki, jak stopień automatyzacji pomiarów, liczbę, geometrię oraz jakość wykorzystywanych obrazów cyfrowych. Dokonano studium literaturowego dotyczącego charakterystyki przetwarzania obrazów, w szczególności obejmującego problematykę automatycznej detekcji narożników (punktów charakterystycznych) oraz modelowania 3D obiektów bliskiego zasięgu. Na podstawie przeprowadzonych analiz, wyodrębniono operatory, które mogą być wykorzystane dla automatycznego wykrywania punktów charakterystycznych obiektu, odwzorowanego na obrazach cyfrowych: Morayeca, Harrisa, Trajkoyica, SUSAN (ang. Smallest Univalue Segment Assimilaling Nucleus), SIFT (ang. Scale Invariant Feature Transform). Dokonano przeglądu algorytmów automatycznego dopasowywania obrazów, ze szczególnym uwzględnieniem metody ABM (ang. Area Base Matching), zintegrowanej z algorytmami stosowanymi w widzeniu maszynowym (ang. Computer Vision). Jako wynik szerokich analiz teoretycznych i eksperymentalnych, do automatycznego generowania przestrzennej chmury punktów zaproponowano ostatecznie następujący pakiet algorytmów: do wykrywania punktów charakterystycznych na obrazach cyfrowych - operator SUSAN; do do pasowywanla obrazów cyfrowych - metody ABM/lmage Dislance (opcjonalnie, w zależności od liczby wykrytych punktów na obrazie cyfrowym), ABM/CC, ABM/LSM; do obliczania tensora, na podstawie dopasowanych punktów charakterystycznych - algorytm RANSAC (ang. Random Simple Consensus). Przeprowadzone analizy i eksperymenty pozwoliły zdefiniować warunki dotyczące geometrii zdjęć, oświetlenia, jakości tekstury obiektu oraz rozdzielczości i formatu obrazu cyfrowego do opracowania autorskiego pakietu algorytmów do automatycznego generowania modeli 3D wybranych obiektów bliskiego zasięgu. Zaprojektowano modułową strukturę prototypu oprogramowania, 2 których każdy realizuje inny etap generowania modelu 3D. Udowodniono, ze dobierając algorytmy wielo obrazowego przetwarzania obrazów cyfrowych, stosowane w środowisku fotogrametrycznym i widzeniu maszynowym, można automatycznie generować powierzchnie wybranych modeli 3D bliskiego zasięgu.

EN

Modelling objects using digital images has been defined as a complete process which starts from image acquisition and is completed by creation of a virtual 3D model. The thesis which has been assumed for the present work is based on the assumption that by using specially selected algorithms applied in photogrammetry and in computer vision (CV), it is possible to perform multi-image, automatic, digital matching of close range images, in order to automatically reconstruct photorealistic 3D models of selected objects. Basing on reviews of Polish and foreign publications, an analysis of existing measuring systems has been performed, which are applied for 3D modelling in close range photogrammetry, The performed analyses considered such factors as: measurement automation level, the number, geometry and quality of applied digital images. The study of publications concerning image processing characteristics, with particular attention paid to automatic detection of corners (characteristic points), as well as 3D modelling of close range objects, has been performed. The analyses allow to select the following algorithms which might be applied for automatic detection of characteristic points of an object, visible on digital images: Moravec, Harris, Trajkovic, SUSAN (Smallest Univalue Segment Assimilating Nucleus), SIFT (Scale Invariant Feature Transform). Algorithms for automatic image matching, with particular consideration of the ABM (Area Base Matching) method, integrated with algorithms applied in computer vision, have also been reviewed. As a result of comprehensive theoretical and experimental analyses, the following package of algorithms has been finally proposed for automatic generation of a spatial point cloud: for detection of characteristic points on digital images - SUSAN algorithm; for digital image matching - successive utilization of the ABM/Image Distance method (as an option, depending on the number of points detected in me digital image), the ABM/CC, ABM/LSM method; for tensor calculations basing on matched characteristic points it is proposed to apply the RANSAC (Random Simple Consensus) algorithm. The performed analyses and experiments allow to define conditions related to image geometry, illumination, texture quality, as well as resolution and formats of digital images with respect to development of the author's package of algorithms for automatic generation of 3D models of selected close range objects. A modular structure of prototype software has been designed, in which every module performs successive stages of the 3D model generation. It was also proved that - after selection of appropriate algorithms of multi-image digital image processing, applied in photogrammetry and computer vision - it is possible to automatically generate surfaces of selected 3D close range models.

Słowa kluczowe

PL

detekcja narożników; automatyczne dopasowanie obrazów; ABM; tensor trójogniskowy; RANSAC; modelowanie 3D

EN

detection of corners; automatic image matching; ABM method; three-focal tensor; RANSAC algorithm; 3D modelling

• Wydawca: Oficyna Wydawnicza Politechniki Warszawskiej
• Czasopismo: Prace Naukowe Politechniki Warszawskiej. Geodezja
• Rocznik: 2013
• Tom: z. 50
• Strony: 5--96
• Opis fizyczny: Bibliogr. 111 poz., rys., tab., wykr.

Twórcy

autor

Zawieska D.

• Wydział Geodezji i Kartografii, Zakład Fotogrametrii, Teledetekcji i Systemów Informacji Przestrzennej

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