3D reconstruction of building facade with fused data of terrestrial LiDAR data and optical image

Yang, Lin; Sheng, Yehua; Wang, Bo

doi:10.1016/j.ijleo.2015.11.147

Cited by 36 publications

(19 citation statements)

References 12 publications

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“…The integration of point clouds and imagery data for detailed building modelling can help to solve the above problems [14,[25][26][27][28][29]. Researchers have made some trials in the integration of multi-source data for reconstructing the building models.…”

Section: Introductionmentioning

confidence: 99%

“…Gruen et al [27] developed a city modelling workflow, which adopted the UAV images to reconstruct the roof surfaces and terrestrial mobile mapping point clouds for the facades. Yang et al [28] combined the terrestrial LiDAR data and image data to achieve a better presentation of building model. These reported methods contribute significantly towards integrated building model reconstruction, but they all mainly focus on data registration and feature fusion, and the automation level of building model reconstruction could be improved.…”

Section: Introductionmentioning

confidence: 99%

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Accurate Reconstruction of the LoD3 Building Model by Integrating Multi-Source Point Clouds and Oblique Remote Sensing Imagery

Xue-dong

Xie

Liu

et al. 2019

IJGI

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3D urban building models, which provide 3D information services for urban planning, management and operational decision-making, are essential for constructing digital cities. Unfortunately, the existing reconstruction approaches for LoD3 building models are insufficient in model details and are associated with a heavy workload, and accordingly they could not satisfy urgent requirements of realistic applications. In this paper, we propose an accurate LoD3 building reconstruction method by integrating multi-source laser point clouds and oblique remote sensing imagery. By combing high-precision plane features extracted from point clouds and accurate boundary constraint features from oblique images, the building mainframe model, which provides an accurate reference for further editing, is quickly and automatically constructed. Experimental results show that the proposed reconstruction method outperforms existing manual and automatic reconstruction methods using both point clouds and oblique images in terms of reconstruction efficiency and spatial accuracy.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Accurate Reconstruction of the LoD3 Building Model by Integrating Multi-Source Point Clouds and Oblique Remote Sensing Imagery

Xue-dong

Xie

Liu

et al. 2019

IJGI

View full text Add to dashboard Cite

show abstract

“…Proliferation in the fields of laser scanning and imaging sensors enable the point clouds, either acquired from light detection and ranging (LiDAR) or photogrammetry, to describe large-area 3D scenes efficiently, providing a good data foundation for building reconstruction with a higher level of detail. LiDAR point clouds with high density and precision, along with the high-resolution images taken at the same time can be obtained, cutting-edge researches involve the fusion of point clouds and image data for extra reliable information [7,8]. The façade point clouds can be utilized to assist the boundary generation with sharp features preserved and automatic LoD3 modeling is now conceivable.…”

Section: Introductionmentioning

confidence: 99%

TopoLAP: Topology Recovery for Building Reconstruction by Deducing the Relationships between Linear and Planar Primitives

et al. 2019

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Limited by the noise, missing data and varying sampling density of the point clouds, planar primitives are prone to be lost during plane segmentation, leading to topology errors when reconstructing complex building models. In this paper, a pipeline to recover the broken topology of planar primitives (TopoLAP) is proposed to reconstruct level of details 3 (LoD3) models. Firstly, planar primitives are segmented from the incomplete point clouds and feature lines are detected both from point clouds and images. Secondly, the structural contours of each plane segment are reconstructed by subset selection from intersections of these feature lines. Subsequently, missing planes are recovered by plane deduction according to the relationships between linear and planar primitives. Finally, the manifold and watertight polyhedral building models are reconstructed based on the optimized PolyFit framework. Experimental results demonstrate that the proposed pipeline can handle partial incomplete point clouds and reconstruct the LoD3 models of complex buildings automatically. A comparative analysis indicates that the proposed method performs better to preserve sharp edges and achieves a higher fitness and correction rate than rooftop-based modeling and the original PolyFit algorithm.

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“…To avoid this drawback, aerial imagery was introduced as supplemental data to improve the accuracy because of its high resolution. Therefore, certain studies have used both LiDAR data and aerial imagery for building reconstruction during the last decade [21][22][23][24][25]. Because of this improved process, building models can incorporate acceptable shape effects, although they are always geometric volumes that disregarded important semantic information about the structures.…”

Section: Introductionmentioning

confidence: 99%

Semantic 3D Modeling Based on CityGML for Ancient Chinese-Style Architectural Roofs of Digital Heritage

Lin

Tang

Zhu

et al. 2017

IJGI

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Ancient Chinese-style architecture has received increased attention during the last century as a segment of cultural heritage and is of great significance, specifically in regard to the process of digitizing and modeling these buildings to preserve and protect this heritage. Because the roof form reflects the age of the structure, the structural character and the historical culture of the ancient building, constructing a refined model for the roof is a primary aspect of the 3D modeling procedure. To avoid cumbersome traditional modeling approaches that use geometry units, such as points, lines and triangles, a flexible semantic method is proposed in this study to improve modeling efficiency and reduce the professional requirements. In this method, a two-level semantic decomposition of the roof is presented according to the characteristics of ancient Chinese-style architecture. The structural level reveals the basic components that determine its structural shape, and the decorative level refers to the attached components that influence the exterior appearance. The assembly validity of the decomposed elements and the combined diversity of the integrated entities are ensured by topological constraints and derived transformations of the semantic components. This proposed method was implemented by utilizing CityGML (City Geography Markup Language) via the ADE (Application Domain Extension) mechanism and was tested by modeling the principal buildings included in the Palace Museum.

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3D reconstruction of building facade with fused data of terrestrial LiDAR data and optical image

Cited by 36 publications

References 12 publications

Accurate Reconstruction of the LoD3 Building Model by Integrating Multi-Source Point Clouds and Oblique Remote Sensing Imagery

Accurate Reconstruction of the LoD3 Building Model by Integrating Multi-Source Point Clouds and Oblique Remote Sensing Imagery

TopoLAP: Topology Recovery for Building Reconstruction by Deducing the Relationships between Linear and Planar Primitives

Semantic 3D Modeling Based on CityGML for Ancient Chinese-Style Architectural Roofs of Digital Heritage

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