A comparison of dense matching algorithms for scaled surface reconstruction using stereo camera rigs

Ahmadabadian, Ali Hosseininaveh; Robson, Stuart; Boehm, J.; Shortis, Mark R.; Wenzel, Konrad; Fritsch, Dieter

doi:10.1016/j.isprsjprs.2013.01.015

Cited by 127 publications

(58 citation statements)

References 25 publications

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“…As other main commercial software aimed to photogrammetric purposes, the Pix4D workflow is based on a Structure From Motion approach (Robertson & Cipolla, 2009;Ahmadabadian et al,2013Roncella et al,2011Del Pizzo et al , 2011;Fritsh et al ., 2011;Fritsh et al ., 2012) of four steps: initial processing, point cloud densification, 3d model realization, DSM and orthomosaic generation. After the initial processing, especially for mapping generation, the GCPs and CPs are inserted in order to check the accuracy of the generated products.…”

Section: Data Processingmentioning

confidence: 99%

TLS Models Generation Assisted by Uav Survey

Chiabrando¹,

Pietra²,

Lingua³

et al. 2016

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

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ABSTRACT:(TLS, Terrestrial Laser Scanning), and large scale mapping derived by UAV (Unmanned Aerial Vehicle) survey. This paper refers an example of 3D survey and reality based modelling applied on landscape and architectural assets. The choice of methods for documentation, in terms of survey techniques, depends primarily on issues and features of the area. The achieved experience, allow to consider that the easy handling of TLS has enabled the use in limited spaces among buildings and collapsed roofs, but the topographic measure of GCPs (Ground Control Points), neither by total station nor by GPS/RTK technique, was easily feasible. Even more than proving the ability of the integration of TLS and UAV photogrammetry to achieve a multisource and multi-scale whole model of a village, the experience has been a test to experiment the registration of terrestrial clouds with the support of control points derived by UAV survey and finally, a comparison among different strategies of clouds registration is reported. Analysing for each approach a number of parameters (number of clouds registration, number of needed points, processing time, overall accuracy) the further comparisons have been achieved. The test revealed that it is possible to decrease the large number of terrestrial control points when their determination by topographical measures is difficult, and it is possible to combine the techniques not only for the integration of the final 3Dmodel, but also to solve and make the initial stage of the drafting process more effective.

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Section: Data Processingmentioning

confidence: 99%

TLS Models Generation Assisted by Uav Survey

Chiabrando¹,

Pietra²,

Lingua³

et al. 2016

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

View full text Add to dashboard Cite

show abstract

“…Many of the dense matching algorithms have been proposed in existing literature; e.g., a comparison of a few of them can be found in Ahmadabadian et al (2013). Their groups vary significantly by underlying assumptions, range of use, and effects.…”

Section: Potential Of Uas Imagerymentioning

confidence: 99%

Experiments With Uas Imagery for Automatic Modeling of Power Line 3d Geometry

Jóźków

Jagt

Toth

2015

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

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Commission I, ICWG I/V-B KEY WORDS: UAS, Dense Matching, Transmission Lines, Modeling ABSTRACT:The ideal mapping technology for transmission line inspection is the airborne LiDAR executed from helicopter platforms. It allows for full 3D geometry extraction in highly automated manner. Large scale aerial images can be also used for this purpose, however, automation is possible only for finding transmission line positions (2D geometry), and the sag needs to be estimated manually. For longer lines, these techniques are less expensive than ground surveys, yet they are still expensive. UAS technology has the potential to reduce these costs, especially if using inexpensive platforms with consumer grade cameras. This study investigates the potential of using high resolution UAS imagery for automatic modeling of transmission line 3D geometry.The key point of this experiment was to employ dense matching algorithms to appropriately acquired UAS images to have points created also on wires. This allowed to model the 3D geometry of transmission lines similarly to LiDAR acquired point clouds. Results showed that the transmission line modeling is possible with a high internal accuracy for both, horizontal and vertical directions, even when wires were represented by a partial (sparse) point cloud.

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“…The inherent deficiencies of DIM point clouds data put great challenges in generating polygons with high geometry accuracy (Ahmadabadian et al, 2013). As summarized by , the quality of photogrammetric point clouds is inferior to that of laser scanning in the level of noise and preservation of sharp features.…”

Section: Introductionmentioning

confidence: 99%

Hierarchical Regularization of Polygons for Photogrammetric Point Clouds of Oblique Images

Xie

Han

Zhu

et al. 2017

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

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ABSTRACT:Despite the success of multi-view stereo (MVS) reconstruction from massive oblique images in city scale, only point clouds and triangulated meshes are available from existing MVS pipelines, which are topologically defect laden, free of semantical information and hard to edit and manipulate interactively in further applications. On the other hand, 2D polygons and polygonal models are still the industrial standard. However, extraction of the 2D polygons from MVS point clouds is still a non-trivial task, given the fact that the boundaries of the detected planes are zigzagged and regularities, such as parallel and orthogonal, cannot preserve. Aiming to solve these issues, this paper proposes a hierarchical polygon regularization method for the photogrammetric point clouds from existing MVS pipelines, which comprises of local and global levels. After boundary points extraction, e.g. using alpha shapes, the local level is used to consolidate the original points, by refining the orientation and position of the points using linear priors. The points are then grouped into local segments by forward searching. In the global level, regularities are enforced through a labeling process, which encourage the segments share the same label and the same label represents segments are parallel or orthogonal. This is formulated as Markov Random Field and solved efficiently. Preliminary results are made with point clouds from aerial oblique images and compared with two classical regularization methods, which have revealed that the proposed method are more powerful in abstracting a single building and is promising for further 3D polygonal model reconstruction and GIS applications.

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A comparison of dense matching algorithms for scaled surface reconstruction using stereo camera rigs

Cited by 127 publications

References 25 publications

TLS Models Generation Assisted by Uav Survey

TLS Models Generation Assisted by Uav Survey

Experiments With Uas Imagery for Automatic Modeling of Power Line 3d Geometry

Hierarchical Regularization of Polygons for Photogrammetric Point Clouds of Oblique Images

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