Façade Reconstruction Using Geometric and Radiometric Point Cloud Information

Tutzauer, Patrick; Haala, Norbert

doi:10.5194/isprsarchives-xl-3-w2-247-2015

Cited by 18 publications

(12 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Such results can be used as input for automatic 3D building reconstruction (Tutzauer and Haala, 2015;Remondino et al, 2016). The dense image matching algorithm implemented in Pix4D was adopted in this study to derive dense point clouds from the Imst data set.…”

Section: Dense Point Cloud Extractionmentioning

confidence: 99%

CHANGING THE PRODUCTION PIPELINE – USE OF OBLIQUE AERIAL CAMERAS FOR MAPPING PURPOSES

Moe¹,

Toschi²,

Poli³

et al. 2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

ABSTRACT:This paper discusses the potential of current photogrammetric multi-head oblique cameras, such as UltraCam Osprey, to improve the efficiency of standard photogrammetric methods for surveying applications like inventory surveys and topographic mapping for public administrations or private customers. In 2015, Terra Messflug (TM), a subsidiary of Vermessung AVT ZT GmbH (Imst, Austria), has flown a number of urban areas in Austria, Czech Republic and Hungary with an UltraCam Osprey Prime multi-head camera system from Vexcel Imaging. In collaboration with FBK Trento (Italy), the data acquired at Imst (a small town in Tyrol, Austria) were analysed and processed to extract precise 3D topographic information. The Imst block comprises 780 images and covers an area of approx. 4.5 km by 1.5 km. Ground truth data is provided in the form of 6 GCPs and several check points surveyed with RTK GNSS. Besides, 3D building data obtained by photogrammetric stereo plotting from a 5 cm nadir flight and a LiDAR point cloud with 10 to 20 measurements per m² are available as reference data or for comparison. The photogrammetric workflow, from flight planning to Dense Image Matching (DIM) and 3D building extraction, is described together with the achieved accuracy. For each step, the differences and innovation with respect to standard photogrammetric procedures based on nadir images are shown, including high overlaps, improved vertical accuracy, and visibility of areas masked in the standard vertical views. Finally the advantages of using oblique images for inventory surveys are demonstrated.

show abstract

Section: Dense Point Cloud Extractionmentioning

confidence: 99%

CHANGING THE PRODUCTION PIPELINE – USE OF OBLIQUE AERIAL CAMERAS FOR MAPPING PURPOSES

Moe¹,

Toschi²,

Poli³

et al. 2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

show abstract

“…Integrated processing of LiDAR and image data [BH07] has been found to be useful to recover the building details. Another recent approach exploits geometric and radiometric point cloud information to enrich the façade details of LOD2 building models [TH15]. In summary, with the increasing availability of coarse models (due to the recent advances in MVS workflows such as Acute3D, Autodesk or Pix4D) in the web‐based applications, there exists a huge scope for refining the quality of such coarse meshes using the information embedded in other widely available input sources such as laser scans or images.…”

Section: Related Workmentioning

confidence: 99%

Enhancing Urban Façades via LiDAR‐Based Sculpting

Peethambaran

Wang

2017

Computer Graphics Forum

View full text Add to dashboard Cite

Buildings with symmetrical façades are ubiquitous in urban landscapes and detailed models of these buildings enhance the visual realism of digital urban scenes. However, a vast majority of the existing urban building models in web‐based 3D maps such as Google earth are either less detailed or heavily rely on texturing to render the details. We present a new framework for enhancing the details of such coarse models, using the geometry and symmetry inferred from the light detection and ranging (LiDAR) scans and 2D templates. The user‐defined 2D templates, referred to as coded planar meshes (CPMs), encodes the geometry of the smallest repeating 3D structures of the façades via face codes. Our encoding scheme, take into account the directions, type as well as the offset distance of the sculpting to be applied at the respective locations on the coarse model. In our approach, LiDAR scan is registered with the coarse models taken from Google earth 3D or Bing maps 3D and decomposed into dominant planar segments (each representing the frontal or lateral walls of the building). The façade segments are then split into horizontal and vertical tiles using a weighted point count function defined over the window or door boundaries. This is followed by an automatic identification of CPM locations with the help of a template fitting algorithm that respects the alignment regularity as well as the inter‐element spacing on the façade layout. Finally, 3D boolean sculpting operations are applied over the boxes induced by CPMs and the coarse model, and a detailed 3D model is generated. The proposed framework is capable of modelling details even with occluded scans and enhances not only the frontal façades (facing to the streets) but also the lateral façades of the buildings. We demonstrate the potentials of the proposed framework by providing several examples of enhanced Google earth models and highlight the advantages of our method when designing photo‐realistic urban façades.

show abstract

“…To evaluate the likelihood that a point lies along a boundary, we can introduce the confidence value and accumulated effect value from [38], but in [38], they used a covariance matrix to calculate the confidence value, which has a high computation complexity, to lower the computation complexity, in our algorithm, we use the method from [39] to evaluate the confidence value. In this method, four categories for the boundary point of window can be distinguished, including upper, lower, left, and right edge points.…”

Section: Floor Analysis and Extractionmentioning

confidence: 99%

A Semantic Modelling Framework-Based Method for Building Reconstruction from Point Clouds

Zhang

et al. 2016

Remote Sensing

View full text Add to dashboard Cite

Abstract:Over the past few years, there has been an increasing need for semantic information in automatic city modelling. However, due to the complexity of building structure, the semantic reconstruction of buildings is still a challenging task because it is difficult to extract architectural rules and semantic information from the data. To improve the insufficiencies, we present a semantic modelling framework-based approach for automated building reconstruction using the semantic information extracted from point clouds or images. In this approach, a semantic modelling framework is designed to describe and generate the building model, and a workflow is established for extracting the semantic information of buildings from an unorganized point cloud and converting the semantic information into the semantic modelling framework. The technical feasibility of our method is validated using three airborne laser scanning datasets, and the results are compared with other related works comprehensively, which indicate that our approach can simplify the reconstruction process from a point cloud and generate 3D building models with high accuracy and rich semantic information.

show abstract

Façade Reconstruction Using Geometric and Radiometric Point Cloud Information

Cited by 18 publications

References 8 publications

CHANGING THE PRODUCTION PIPELINE – USE OF OBLIQUE AERIAL CAMERAS FOR MAPPING PURPOSES

CHANGING THE PRODUCTION PIPELINE – USE OF OBLIQUE AERIAL CAMERAS FOR MAPPING PURPOSES

Enhancing Urban Façades via LiDAR‐Based Sculpting

A Semantic Modelling Framework-Based Method for Building Reconstruction from Point Clouds

Contact Info

Product

Resources

About

Façade Reconstruction Using Geometric and Radiometric Point Cloud Information

Cited by 18 publications

References 8 publications

CHANGING THE PRODUCTION PIPELINE &ndash; USE OF OBLIQUE AERIAL CAMERAS FOR MAPPING PURPOSES

CHANGING THE PRODUCTION PIPELINE &ndash; USE OF OBLIQUE AERIAL CAMERAS FOR MAPPING PURPOSES

Enhancing Urban Façades via LiDAR‐Based Sculpting

A Semantic Modelling Framework-Based Method for Building Reconstruction from Point Clouds

Contact Info

Product

Resources

About

CHANGING THE PRODUCTION PIPELINE – USE OF OBLIQUE AERIAL CAMERAS FOR MAPPING PURPOSES

CHANGING THE PRODUCTION PIPELINE – USE OF OBLIQUE AERIAL CAMERAS FOR MAPPING PURPOSES