Refinement of semantic 3D building models by reconstructing underpasses from MLS point clouds

Wysocki, Olaf; Hoegner, L.; Stilla, Uwe

doi:10.1016/j.jag.2022.102841

Cited by 8 publications

(18 citation statements)

References 38 publications

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“…In contrast to our previous work devoted to refining building models with underpasses (Wysocki et al, 2022a), in this paper we focus on detecting and reconstructing outstanding fac ¸ade openings, such as windows and doors. Moreover, our method refines point cloud segmentation by back-projecting classified conflicts onto the input point clouds.…”

Section: Methodsmentioning

confidence: 99%

“…These are back-projected to the point cloud, refining its segmentation accuracy. If the Bayesian network detects windows or doors, shape extraction is conducted (Section 3.7); otherwise, another module can be triggered, such as the underpass reconstruction (Wysocki et al, 2022a). Opening shape extraction is followed by shape generalization, which delineates fitting borders for 3D reconstruction (Section 3.7).…”

Section: Methodsmentioning

confidence: 99%

“…In our previous work (Wysocki et al, 2022a), we introduced visibility analysis to refine semantic 3D building models with underpasses using MLS point clouds. The method compares ray-traced points with building objects on an octree grid in a probabilistic fashion.…”

Section: Visibility Analysis Using Point Cloudsmentioning

confidence: 99%

“…On the other hand, points' rays intersecting with 3D models can provide geometrical cues about possible fac ¸ade openings, but without differentiating between classes, such as window, door, or underpass (Tuttas and Stilla, 2013). In this paper, we present a strategy that combines both ray-and region-based methods for conflict classification (Wysocki et al, 2022a). This approach leads to refinement of both 3D building models and segmented point clouds' accuracy; our contributions are as follows:…”

Section: Introductionmentioning

confidence: 99%

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Combining Visibility Analysis and Deep Learning for Refinement of Semantic 3d Building Models by Conflict Classification

Wysocki

Grilli

Hoegner

et al. 2022

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Semantic 3D building models are widely available and used in numerous applications. Such 3D building models display rich semantics but no façade openings, chiefly owing to their aerial acquisition techniques. Hence, refining models’ façades using dense, street-level, terrestrial point clouds seems a promising strategy. In this paper, we propose a method of combining visibility analysis and neural networks for enriching 3D models with window and door features. In the method, occupancy voxels are fused with classified point clouds, which provides semantics to voxels. Voxels are also used to identify conflicts between laser observations and 3D models. The semantic voxels and conflicts are combined in a Bayesian network to classify and delineate façade openings, which are reconstructed using a 3D model library. Unaffected building semantics is preserved while the updated one is added, thereby upgrading the building model to LoD3. Moreover, Bayesian network results are back-projected onto point clouds to improve points’ classification accuracy. We tested our method on a municipal CityGML LoD2 repository and the open point cloud datasets: TUM-MLS-2016 and TUM-FAÇADE. Validation results revealed that the method improves the accuracy of point cloud semantic segmentation and upgrades buildings with façade elements. The method can be applied to enhance the accuracy of urban simulations and facilitate the development of semantic segmentation algorithms.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Visibility Analysis Using Point Cloudsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Combining Visibility Analysis and Deep Learning for Refinement of Semantic 3d Building Models by Conflict Classification

Wysocki

Grilli

Hoegner

et al. 2022

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…In the absence of beams, the net height requirement of the bridge under the bridge can be minimized so that it will reduce the volume of excavation. The bridge plate is then designed to be integrated with the pillars of the retaining sheet pile so that in this position the sheet pile will receive the load from the side soil pressure and will also receive and transmit the load from the bridge slab plate (Brehme et al, 2021;Jiang et al, 2022;Wysocki et al, 2022). Calculation of internal forces until the reinforcement design is obtained for both the sheet pile construction and the superstructure and substructure of the bridge will be carried out using SAP 2000 v.14 software.…”

Section: Methodsmentioning

confidence: 99%

Study of the under pass structure in Gatot Subroto – Cokroaminoto Intersection-Roads, Denpasar – Bali

Jaya

Sutapa

Suasira

et al. 2022

irjeis

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Denpasar represent town with amount of most resident in Bali and have tendency will increasingly. This of course will be followed by accelerating development various sector. This condition will be create various of urban problems, among the others problem is jam of traffic, that caused of existence of unbalanced between growth of very fast vehicle (14%) compared to with accretion of new streets which only reaching 3,6% a year. To overcome the problem one of the effort able to be conducted is by improving the quality of street service which have there, especially at critical joint streets and intersection streets, like Gatot Subroto - Cokroaminoto intersection-roads. However progressively is fast of accretion amount of vehicle, this methode will not can give optimal service, so that require to another way of problem solving. Other Arrangement Alternative to solve this jam is with intersection street is not at a piece of, such as which have been applied at Simpang Dewa Ruci. In general, the type of construction is fly over and underpass, but pursuant to experience at Simpang Dewa Ruci, from the social and culture aspect happened deduction of fly over type.

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3D Modeling of Façade Elements Using Multi-View Images from Mobile Scanning Systems

Salehitangrizi,

Jabari,

Sheng

et al. 2024

Canadian Journal of Remote Sensing

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Refinement of semantic 3D building models by reconstructing underpasses from MLS point clouds

Cited by 8 publications

References 38 publications

Combining Visibility Analysis and Deep Learning for Refinement of Semantic 3d Building Models by Conflict Classification

Combining Visibility Analysis and Deep Learning for Refinement of Semantic 3d Building Models by Conflict Classification

Study of the under pass structure in Gatot Subroto – Cokroaminoto Intersection-Roads, Denpasar – Bali

3D Modeling of Façade Elements Using Multi-View Images from Mobile Scanning Systems

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