3D building reconstruction from aerial CCD image and sparse laser sample data

You, Hongjian; Zhang, Shiqiang

doi:10.1016/j.optlaseng.2005.06.004

Cited by 29 publications

(12 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…List of ISI-indexed publications that provide accuracy measures within the publication along with additional information derived from the articles on additional data sources and on the accuracy assessments. Some authors [15,21,47,48,54,[82][83][84][85][86][87][88] exclusively rely on visual comparisons or provide no explicit accuracy measure, thus making it difficult to quantitatively evaluate the quality of the developed approach based on the respective article only. We can observe that all of the approaches, which reported some kind of accuracy measure resulted in relatively high accuracies (>76%).…”

Section: Analysis Of Gathered Building Extraction Accuraciesmentioning

confidence: 99%

“…Depending on the author and the developed methodology, the source of additional data varied. This additional data included aerial images [16,19,20,44,[50][51][52][60][61][62]86,[93][94][95], multi-spectral imagery [53,55,57,58,63], purely infrared spectral image [64] or 2D ground plans [35].…”

Section: Use Of Auxiliary Data For Building Object Extractionmentioning

confidence: 99%

“…The authors of [20] used imagery as the source for a NDVI and texture calculation, and also as one of the data sources for segmentation. Hongjian et al The authors of [86] used aerial imagery in order to determine the geometrical shape of a building and to extract the building edges based on the Laplacian sharpening operator and threshold segmentation. Kabolizade et al [61] used the canny edge detection operator in order to extract building edges and as an input for the improved snake model.…”

Section: Use Of Auxiliary Data For Building Object Extractionmentioning

confidence: 99%

See 2 more Smart Citations

Building Extraction from Airborne Laser Scanning Data: An Analysis of the State of the Art

et al. 2015

View full text Add to dashboard Cite

Abstract:This article provides an overview of building extraction approaches applied to Airborne Laser Scanning (ALS) data by examining elements used in original publications, such as data set area, accuracy measures, reference data for accuracy assessment, and the use of auxiliary data. We succinctly analyzed the most cited publication for each year between 1998 and 2014, resulting in 54 ISI-indexed articles and 14 non-ISI indexed publications. Based on this, we position some built-in features of ALS to create a comprehensive picture of the state of the art and the progress through the years. Our analyses revealed trends and remaining challenges that impact the community. The results show remaining deficiencies, such as inconsistent accuracy assessment measures, limitations of independent reference data sources for accuracy assessment, relatively few documented applications of the methods to wide area data sets, and the lack of transferability studies and measures. Finally, we predict some future trends and identify some gaps which existing approaches may not exhaustively cover. Despite these deficiencies, this comprehensive literature analysis demonstrates that ALS data is certainly a valuable source of spatial information for building extraction. When taking into account the short civilian history of ALS one can conclude that ALS has become well established in the scientific community and seems to become indispensable in many application fields.

show abstract

Section: Analysis Of Gathered Building Extraction Accuraciesmentioning

confidence: 99%

Section: Use Of Auxiliary Data For Building Object Extractionmentioning

confidence: 99%

Section: Use Of Auxiliary Data For Building Object Extractionmentioning

confidence: 99%

See 1 more Smart Citation

Building Extraction from Airborne Laser Scanning Data: An Analysis of the State of the Art

et al. 2015

View full text Add to dashboard Cite

show abstract

“…Google Earth [21], the French National Geographic Institute (IGN) [22,23] and other authors [24][25][26] also propose frameworks used to rebuild the geometry of real urban scenes based on various types of images (satellite, aerial, ground, etc.). Again, no topological information is produced with these approaches.…”

Section: Analysis Of Architectural Bitmap Imagesmentioning

confidence: 99%

Consistency constraints and 3D building reconstruction

Horna

Méneveaux

Damiand

et al. 2009

Computer-Aided Design

View full text Add to dashboard Cite

a b s t r a c tVirtual architectural (indoor) scenes are often modeled in 3D for various types of simulation systems. For instance, some authors propose methods dedicated to lighting, heat transfer, acoustic or radiowave propagation simulations. These methods rely in most cases on a volumetric representation of the environment, with adjacency and incidence relationships. Unfortunately, many buildings data are only given by 2D plans and the 3D needs varies from one application to another. To face these problems, we propose a formal representation of consistency constraints dedicated to building interiors and associated with a topological model. We show that such a representation can be used for: (i) reconstructing 3D models from 2D architectural plans (ii) detecting automatically geometrical, topological and semantical inconsistencies (iii) designing automatic and semi-automatic operations to correct and enrich a 2D plan. All our constraints are homogeneously defined in 2D and 3D, implemented with generalized maps and used in modeling operations. We explain how this model can be successfully used for lighting and radiowave propagation simulations.

show abstract

“…As reported by Hongjiana and Shiqiang (2006), another approach involves extracting the data and connecting edge pixels. This allows for the derivation of building heights from sparse laser samples and can be used to reconstruct 3D information for each building.…”

Section: Introductionmentioning

confidence: 99%