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Titel:3D Reconstruction using Active Illumination
Autor:Grochulla, Martin
Weitere Beteiligte: Thormählen, Thorsten (Prof. Dr.)
Veröffentlicht:2017
URI:https://archiv.ub.uni-marburg.de/diss/z2017/0050
DOI: https://doi.org/10.17192/z2017.0050
URN: urn:nbn:de:hebis:04-z2017-00501
DDC: Informatik
Titel(trans.):3D-Rekonstruktion mit Hilfe aktiver Beleuchtung
Publikationsdatum:2017-01-17
Lizenz:https://rightsstatements.org/vocab/InC-NC/1.0/

Dokument

Schlagwörter:
Kamerakalibrierung, Bildverarbeitung, camera calibration, 3D reconstruction, Computervisualistik, 3D-Rekonstruktion

Summary:
In this thesis we present a pipeline for 3D model acquisition. Generating 3D models of real-world objects is an important task in computer vision with many applications, such as in 3D design, archaeology, entertainment, and virtual or augmented reality. The contribution of this thesis is threefold: we propose a calibration procedure for the cameras, we describe an approach for capturing and processing photometric normals using gradient illuminations in the hardware set-up, and finally we present a multi-view photometric stereo 3D reconstruction method. In order to obtain accurate results using multi-view and photometric stereo reconstruction, the cameras are calibrated geometrically and photometrically. For acquiring data, a light stage is used. This is a hardware set-up that allows to control the illumination during acquisition. The procedure used to generate appropriate illuminations and to process the acquired data to obtain accurate photometric normals is described. The core of the pipeline is a multi-view photometric stereo reconstruction method. In this method, we first generate a sparse reconstruction using the acquired images and computed normals. In the second step, the information from the normal maps is used to obtain a dense reconstruction of an object’s surface. Finally, the reconstructed surface is filtered to remove artifacts introduced by the dense reconstruction step.

Zusammenfassung:
In dieser Arbeit präsentieren wir eine Pipeline zur Aufnahme von 3D-Modellen. Die Erzeugung von 3D-Modellen von realen Objekten ist eine wichtige Aufgabe in der Computer Vision mit zahlreichen Anwendungen, wie zum Beispiel 3D-Design, Archäologie und virtueller oder auch erweiterter Realität. Die vorliegende Arbeit liefert drei Beiträge: wir stellen eine Methode zur Kalibrierung von Kameras vor, wir beschreiben einen Ansatz zur Aufnahme und Verarbeitung von photometrischen Normalen, die mit Hilfe von Gradientenbeleuch- tung in der Hardwarekonfiguration aufgenommen worden sind, und schließlich präsentieren wir eine Methode zur Stereorekonstruktion von 3D-Modellen aus photometrischen Daten und mehreren Perspektiven. Um möglichst genaue Rekonstruktionsergebnisse aus mehreren Perspektiven mit Hilfe von photometrischen Daten zu erhalten, werden die Kameras sowohl geometrisch als auch photometrisch kalibriert. Zur Datenaufnahme wird eine sogenannte “Light Stage” benutzt. Dies ist eine Hardwarekonfiguration, die es erlaubt die Beleuchtung während der Aufnahme vollsändig zu kontrollieren. Die verwendete Methode zur Erzeugung der Gradientenbeleuchtung und zur Verarbeitung der aufgenommenen Daten zur Erzeugung genauer photometrischer Normalen wird beschrieben. Der Hauptbestandteil der Pipeline ist eine Methode zur Stereorekonstruktion aus photometrischen Daten und mehreren Perspektiven. Bei dieser Methode erzeugen wir zunächst eine grobe Rekonstruktion mit Hilfe der aufgenommenen Bilder und erzeugten Normalen. In einem zweiten Schritt werden die Normaleninformationen verwendet um eine vollständige Rekonstruktion der Objektoberfläche zu erhalten. Schließlich erfolgt eine Filterung der rekonstruierten Oberfläche, um Artefakte aus dem zweiten Rekonstruktionsschritt zu entfernen.

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