Vectorizing Planar Roof Structure From Very High Resolution Remote Sensing Images Using Transformers

Wufan Zhao; Claudio Persello; Xianwei Lv; Alfred Stein

doi:10.1109/IGARSS52108.2023.10282198

Vectorizing Planar Roof Structure From Very High Resolution Remote Sensing Images Using Transformers

Wufan Zhao^*
, Claudio Persello
, Xianwei Lv
, Alfred Stein

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

57 Downloads (Pure)

Abstract

Grasping the roof structure of a building is a key part of building reconstruction. Directly predicting the geometric structure of the roof from a raster image to a vectorized representation, however, remains challenging. This paper introduces an efficient and accurate parsing method based upon a vision Transformer we dubbed Roof-Former. Our method consists of three steps: 1) Image encoder and edge node initialization, 2) Image feature fusion with an enhanced segmentation refinement branch, and 3) Edge filtering and structural reasoning. The vertex and edge heat map F1-scores have increased by 2.0% and 1.9% on the VWB dataset when compared to HEAT. Additionally, qualitative evaluations suggest that our method is superior to the current state-of-the-art. It indicates effectiveness for extracting global image information and maintaining the consistency and topological validity of the roof structure.

Original language	English
Title of host publication	IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings
Publisher	IEEE
Pages	4899-4902
Number of pages	4
ISBN (Electronic)	9798350320107
DOIs	https://doi.org/10.1109/IGARSS52108.2023.10282198
Publication status	Published - 2023
Event	43rd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023 - Pasadena Convention Center, Pasadena, United States Duration: 16 Jul 2023 → 21 Jul 2023 Conference number: 43 https://2023.ieeeigarss.org/index.php

Publication series

Name	International Geoscience and Remote Sensing Symposium (IGARSS)
Volume	2023-July

Conference

Conference	43rd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023
Abbreviated title	IGARSS 2023
Country/Territory	United States
City	Pasadena
Period	16/07/23 → 21/07/23
Internet address	https://2023.ieeeigarss.org/index.php

Keywords

geometry reconstruction
remote sensing image
Roof structure extraction
Transformer
2024 OA procedure

Access to Document

10.1109/IGARSS52108.2023.10282198

Vectorizing_Planar_Roof_Structure_From_Very_High_Resolution_Remote_Sensing_Images_Using_TransformersFinal published version, 10.7 MBLicence: Taverne

1 Article

Vectorizing planar roof structure from very high resolution remote sensing images using transformers
Zhao, W., Persello, C., Lv, X., Stein, A. & Vergauwen, M., 2024, In: International journal of digital earth. 17, 1, p. 1-15 15 p.
Research output: Contribution to journal › Article › Academic › peer-review

Open Access
File
7 Citations (Scopus)

257 Downloads (Pure)

Cite this

Zhao, W., Persello, C., Lv, X., & Stein, A. (2023). Vectorizing Planar Roof Structure From Very High Resolution Remote Sensing Images Using Transformers. In IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings (pp. 4899-4902). (International Geoscience and Remote Sensing Symposium (IGARSS); Vol. 2023-July). IEEE. https://doi.org/10.1109/IGARSS52108.2023.10282198

@inproceedings{6dfc7ca52c7b41bdb4c4a47fc5dc41f1,

title = "Vectorizing Planar Roof Structure From Very High Resolution Remote Sensing Images Using Transformers",

abstract = "Grasping the roof structure of a building is a key part of building reconstruction. Directly predicting the geometric structure of the roof from a raster image to a vectorized representation, however, remains challenging. This paper introduces an efficient and accurate parsing method based upon a vision Transformer we dubbed Roof-Former. Our method consists of three steps: 1) Image encoder and edge node initialization, 2) Image feature fusion with an enhanced segmentation refinement branch, and 3) Edge filtering and structural reasoning. The vertex and edge heat map F1-scores have increased by 2.0\% and 1.9\% on the VWB dataset when compared to HEAT. Additionally, qualitative evaluations suggest that our method is superior to the current state-of-the-art. It indicates effectiveness for extracting global image information and maintaining the consistency and topological validity of the roof structure.",

keywords = "geometry reconstruction, remote sensing image, Roof structure extraction, Transformer, 2024 OA procedure",

author = "Wufan Zhao and Claudio Persello and Xianwei Lv and Alfred Stein",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 43rd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023, IGARSS 2023 ; Conference date: 16-07-2023 Through 21-07-2023",

year = "2023",

doi = "10.1109/IGARSS52108.2023.10282198",

language = "English",

series = "International Geoscience and Remote Sensing Symposium (IGARSS)",

publisher = "IEEE",

pages = "4899--4902",

booktitle = "IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings",

address = "United States",

url = "https://2023.ieeeigarss.org/index.php",

}

Zhao, W, Persello, C, Lv, X & Stein, A 2023, Vectorizing Planar Roof Structure From Very High Resolution Remote Sensing Images Using Transformers. in IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings. International Geoscience and Remote Sensing Symposium (IGARSS), vol. 2023-July, IEEE, pp. 4899-4902, 43rd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023, Pasadena, California, United States, 16/07/23. https://doi.org/10.1109/IGARSS52108.2023.10282198

Vectorizing Planar Roof Structure From Very High Resolution Remote Sensing Images Using Transformers. / Zhao, Wufan; Persello, Claudio; Lv, Xianwei et al.
IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings. IEEE, 2023. p. 4899-4902 (International Geoscience and Remote Sensing Symposium (IGARSS); Vol. 2023-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Vectorizing Planar Roof Structure From Very High Resolution Remote Sensing Images Using Transformers

AU - Zhao, Wufan

AU - Persello, Claudio

AU - Lv, Xianwei

AU - Stein, Alfred

N1 - Conference code: 43

PY - 2023

Y1 - 2023

N2 - Grasping the roof structure of a building is a key part of building reconstruction. Directly predicting the geometric structure of the roof from a raster image to a vectorized representation, however, remains challenging. This paper introduces an efficient and accurate parsing method based upon a vision Transformer we dubbed Roof-Former. Our method consists of three steps: 1) Image encoder and edge node initialization, 2) Image feature fusion with an enhanced segmentation refinement branch, and 3) Edge filtering and structural reasoning. The vertex and edge heat map F1-scores have increased by 2.0% and 1.9% on the VWB dataset when compared to HEAT. Additionally, qualitative evaluations suggest that our method is superior to the current state-of-the-art. It indicates effectiveness for extracting global image information and maintaining the consistency and topological validity of the roof structure.

AB - Grasping the roof structure of a building is a key part of building reconstruction. Directly predicting the geometric structure of the roof from a raster image to a vectorized representation, however, remains challenging. This paper introduces an efficient and accurate parsing method based upon a vision Transformer we dubbed Roof-Former. Our method consists of three steps: 1) Image encoder and edge node initialization, 2) Image feature fusion with an enhanced segmentation refinement branch, and 3) Edge filtering and structural reasoning. The vertex and edge heat map F1-scores have increased by 2.0% and 1.9% on the VWB dataset when compared to HEAT. Additionally, qualitative evaluations suggest that our method is superior to the current state-of-the-art. It indicates effectiveness for extracting global image information and maintaining the consistency and topological validity of the roof structure.

KW - geometry reconstruction

KW - remote sensing image

KW - Roof structure extraction

KW - Transformer

KW - 2024 OA procedure

U2 - 10.1109/IGARSS52108.2023.10282198

DO - 10.1109/IGARSS52108.2023.10282198

M3 - Conference contribution

AN - SCOPUS:85178369209

T3 - International Geoscience and Remote Sensing Symposium (IGARSS)

SP - 4899

EP - 4902

BT - IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings

PB - IEEE

T2 - 43rd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023

Y2 - 16 July 2023 through 21 July 2023

ER -

Vectorizing Planar Roof Structure From Very High Resolution Remote Sensing Images Using Transformers

Abstract

Publication series

Conference

Keywords

Access to Document

Fingerprint

Research output

Vectorizing planar roof structure from very high resolution remote sensing images using transformers

Cite this