A Planar Feature-Preserving Texture Defragmentation Method for 3D Urban Building Models

Oblique photogrammetry-based 3D modeling is widely used for large-scale urban reconstruction. However, textures generated with photogrammetric techniques often exhibit scattered and irregular characteristics, which lead to significant challenges with texture seams and UV map discontinuities, increas...

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Main Authors: Beining Liu, Wenxuan Liu, Zhen Lei, Fan Zhang, Xianfeng Huang, Tarek M. Awwad
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/16/22/4154
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author Beining Liu
Wenxuan Liu
Zhen Lei
Fan Zhang
Xianfeng Huang
Tarek M. Awwad
author_facet Beining Liu
Wenxuan Liu
Zhen Lei
Fan Zhang
Xianfeng Huang
Tarek M. Awwad
author_sort Beining Liu
collection DOAJ
description Oblique photogrammetry-based 3D modeling is widely used for large-scale urban reconstruction. However, textures generated with photogrammetric techniques often exhibit scattered and irregular characteristics, which lead to significant challenges with texture seams and UV map discontinuities, increasing storage requirements and affecting rendering quality. In this paper, we propose a planar feature-preserving texture defragmentation method designed specifically for urban building models. Our approach leverages the multi-planar topology of buildings to optimize texture merging and reduce fragmentation. The proposed approach is composed of three main stages: the extraction of planar features from texture fragments; the employment of these planar elements as guiding constraints for merging adjacent texture fragments within a two-dimensional texture space; and an enhanced texture-packing algorithm designed for more regular texture charts to systematically generate refined texture atlas. Experiments on various urban building models demonstrate that our method significantly improves texture continuity and storage efficiency compared to traditional approaches, with both quantitative and qualitative validation.
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spelling doaj-art-70ddd828614e427e9564e6365e0fcfbf2025-08-20T02:27:38ZengMDPI AGRemote Sensing2072-42922024-11-011622415410.3390/rs16224154A Planar Feature-Preserving Texture Defragmentation Method for 3D Urban Building ModelsBeining Liu0Wenxuan Liu1Zhen Lei2Fan Zhang3Xianfeng Huang4Tarek M. Awwad5State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, ChinaWuhan Daspatial Technology Co., Ltd., Wuhan 430223, ChinaState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, ChinaState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, ChinaState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, ChinaDepartment of Civil Engineering, Engineering College, Northern Border University, Arar 91431, Saudi ArabiaOblique photogrammetry-based 3D modeling is widely used for large-scale urban reconstruction. However, textures generated with photogrammetric techniques often exhibit scattered and irregular characteristics, which lead to significant challenges with texture seams and UV map discontinuities, increasing storage requirements and affecting rendering quality. In this paper, we propose a planar feature-preserving texture defragmentation method designed specifically for urban building models. Our approach leverages the multi-planar topology of buildings to optimize texture merging and reduce fragmentation. The proposed approach is composed of three main stages: the extraction of planar features from texture fragments; the employment of these planar elements as guiding constraints for merging adjacent texture fragments within a two-dimensional texture space; and an enhanced texture-packing algorithm designed for more regular texture charts to systematically generate refined texture atlas. Experiments on various urban building models demonstrate that our method significantly improves texture continuity and storage efficiency compared to traditional approaches, with both quantitative and qualitative validation.https://www.mdpi.com/2072-4292/16/22/4154photogrammetric building modeltexture reconstructionplane detectionatlas packing
spellingShingle Beining Liu
Wenxuan Liu
Zhen Lei
Fan Zhang
Xianfeng Huang
Tarek M. Awwad
A Planar Feature-Preserving Texture Defragmentation Method for 3D Urban Building Models
Remote Sensing
photogrammetric building model
texture reconstruction
plane detection
atlas packing
title A Planar Feature-Preserving Texture Defragmentation Method for 3D Urban Building Models
title_full A Planar Feature-Preserving Texture Defragmentation Method for 3D Urban Building Models
title_fullStr A Planar Feature-Preserving Texture Defragmentation Method for 3D Urban Building Models
title_full_unstemmed A Planar Feature-Preserving Texture Defragmentation Method for 3D Urban Building Models
title_short A Planar Feature-Preserving Texture Defragmentation Method for 3D Urban Building Models
title_sort planar feature preserving texture defragmentation method for 3d urban building models
topic photogrammetric building model
texture reconstruction
plane detection
atlas packing
url https://www.mdpi.com/2072-4292/16/22/4154
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