Moehrle, Nils (2014)
Texturing 3D Reconstructions from High-Resolution Multi-Scale Images.
Technische Universität Darmstadt
Bachelorarbeit, Bibliographie
Kurzbeschreibung (Abstract)
Texturing is typically the last step within the pipeline for 3D object reconstruction. In the last decade image based 3D reconstruction algorithms became robust and efficient enough to reconstruct even large and unconstrained scenes. However, texturing algorithms struggle with such datasets. This work introduces an algorithm that creates a high quality texture for the resulting meshes of such datasets. Based on Lempitsky and Ivanov's work 19 we use graph cuts to simultaneously select an appropriate view for each face and minimize visible seams. Within the view selection we account for sharpness, resolution and distance of the view as well as the viewing angle. In order to handle the remaining visible seams we use a global seam leveling procedure to adjust color values of the texture patches. Apart from this adjustment we do not blend or resample the input images in any way such that the resulting texture patches have almost identical quality compared to the input images. The algorithm handles datasets with more than 500 high resolution images and meshes with over 8 million triangles in a few hours.
| Typ des Eintrags: | Bachelorarbeit |
|---|---|
| Erschienen: | 2014 |
| Autor(en): | Moehrle, Nils |
| Art des Eintrags: | Bibliographie |
| Titel: | Texturing 3D Reconstructions from High-Resolution Multi-Scale Images |
| Sprache: | Englisch |
| Publikationsjahr: | 2014 |
| Kurzbeschreibung (Abstract): | Texturing is typically the last step within the pipeline for 3D object reconstruction. In the last decade image based 3D reconstruction algorithms became robust and efficient enough to reconstruct even large and unconstrained scenes. However, texturing algorithms struggle with such datasets. This work introduces an algorithm that creates a high quality texture for the resulting meshes of such datasets. Based on Lempitsky and Ivanov's work 19 we use graph cuts to simultaneously select an appropriate view for each face and minimize visible seams. Within the view selection we account for sharpness, resolution and distance of the view as well as the viewing angle. In order to handle the remaining visible seams we use a global seam leveling procedure to adjust color values of the texture patches. Apart from this adjustment we do not blend or resample the input images in any way such that the resulting texture patches have almost identical quality compared to the input images. The algorithm handles datasets with more than 500 high resolution images and meshes with over 8 million triangles in a few hours. |
| Freie Schlagworte: | Mesh segmentation, Texture mapping, Graph cuts, Surface parameterization |
| Zusätzliche Informationen: | 66 p. |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Graphisch-Interaktive Systeme |
| Hinterlegungsdatum: | 12 Nov 2018 11:16 |
| Letzte Änderung: | 12 Nov 2018 11:16 |
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