Reconstructing facade details using MLS point clouds and Bag-of-Words approach
Fuente:
arXiv
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866911774226251776 |
|---|---|
| author | Froech, Thomas Wysocki, Olaf Hoegner, Ludwig Stilla, Uwe |
| author_facet | Froech, Thomas Wysocki, Olaf Hoegner, Ludwig Stilla, Uwe |
| contents | In the reconstruction of façade elements, the identification of specific object types remains challenging and is often circumvented by rectangularity assumptions or the use of bounding boxes. We propose a new approach for the reconstruction of 3D façade details. We combine MLS point clouds and a pre-defined 3D model library using a BoW concept, which we augment by incorporating semi-global features. We conduct experiments on the models superimposed with random noise and on the TUM-FAÇADE dataset. Our method demonstrates promising results, improving the conventional BoW approach. It holds the potential to be utilized for more realistic facade reconstruction without rectangularity assumptions, which can be used in applications such as testing automated driving functions or estimating façade solar potential. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_06521 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Reconstructing facade details using MLS point clouds and Bag-of-Words approach Froech, Thomas Wysocki, Olaf Hoegner, Ludwig Stilla, Uwe Computer Vision and Pattern Recognition Machine Learning In the reconstruction of façade elements, the identification of specific object types remains challenging and is often circumvented by rectangularity assumptions or the use of bounding boxes. We propose a new approach for the reconstruction of 3D façade details. We combine MLS point clouds and a pre-defined 3D model library using a BoW concept, which we augment by incorporating semi-global features. We conduct experiments on the models superimposed with random noise and on the TUM-FAÇADE dataset. Our method demonstrates promising results, improving the conventional BoW approach. It holds the potential to be utilized for more realistic facade reconstruction without rectangularity assumptions, which can be used in applications such as testing automated driving functions or estimating façade solar potential. |
| title | Reconstructing facade details using MLS point clouds and Bag-of-Words approach |
| topic | Computer Vision and Pattern Recognition Machine Learning |
| url | https://arxiv.org/abs/2402.06521 |