Depth texture synthesis for high resolution seamless reconstruction of large scenes

Authors: Labrie-Larrivée, Félix
Advisor: Lalonde, Jean-FrançoisLaurendeau, Denis
Abstract: Large scenes such as building facades are challenging environments for 3D reconstruction. These scenes often include repeating elements (windows, bricks, wood paneling) that can be exploited for the task of 3D reconstruction. Our approach, Depth Texture Synthesis, is based on that idea and aims to improve the quality of 3D model representation of large scenes. By scanning a sample of a repeating structure using a RGBD sensor, Depth Texture Synthesis can propagate the high resolution of that sample to similar parts of the scene. It does so following RGB and low resolution depth information of a SfM reconstruction. To handle this information the building facade is simplified into a planar primitive and serves as our canvas. The high resolution depth of the Kinect sample and low resolution depth of the SfM model as well as the RGB information are projected onto the canvas. Then, powerful image based texture synthesis algorithms are used to propagate the high resolution depth following cues in RGB and low resolution depth. The resulting synthesized high resolution depth is converted back into a 3D model that greatly improves on the SfM model with more detailed, more realistic looking geometry. Our approach is also much less labor intensive than RGBD sensors in large scenes and it is much more affordable than Lidar.
Document Type: Mémoire de maîtrise
Issue Date: 2018
Open Access Date: 9 July 2018
Grantor: Université Laval
Collection:Thèses et mémoires

Files in this item:
33811.pdf195.95 MBAdobe PDFView/Open
All documents in CorpusUL are protected by Copyright Act of Canada.