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Incremental Online Reconstruction of Locally Quadric Surfaces

Title data

Bloeß, Josua ; Henrich, Dominik:
Incremental Online Reconstruction of Locally Quadric Surfaces.
In: Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022). Volume 1. GRAPP. - Setúbal : SciTePress , 2022 . - pp. 155-162
ISBN 978-989-758-555-5
DOI: https://doi.org/10.5220/0010795100003124

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Abstract in another language

Representing surfaces of a digital 3D model using high level geometric information is key to lots of geometric processing and other use cases. In order to obtain these 3D models, various scanning methods have been proposed. We contribute a method for incremental reconstruction of surfaces from a series of point clouds.
For this, we use a robust over-segmentation technique on a point cloud and build a memory efficient graph structure upon it. Over time, we expand this graph structure as global representation. We also propose a fast fitting algorithm for quadric surface patches to the graph structure. We validate the overall performance in our experiments.

Further data

Item Type: Article in a book
Refereed: Yes
Keywords: Reconstruction; Segmentation; Point cloud; Surface fitting; Quadrics; Online computation; 3D-image processing
Institutions of the University: Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Applied Computer Science III > Chair Applied Computer Science III - Univ.-Prof. Dr. Dominik Henrich
Faculties
Faculties > Faculty of Mathematics, Physics und Computer Science
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Applied Computer Science III
Result of work at the UBT: Yes
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
Date Deposited: 14 Feb 2025 10:02
Last Modified: 15 Apr 2025 11:35
URI: https://eref.uni-bayreuth.de/id/eprint/92333