Building Footprints Extraction from Oblique Imagery

Nex, Francesco; Rupnik, Ewelina; Remondino, Fabio

doi:10.5194/isprsannals-ii-3-w3-61-2013

Cited by 32 publications

(25 citation statements)

References 19 publications

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“…Different algorithms, primarily developed for the purpose of matching nadir images, have also been tested for use with oblique images, for example, Semi Global Matching (Gerke, 2009) and MicMac (Nex et al, 2013). New methods have also been developed and modified (Fritsch and Rothermel, 2013;Zhang et al, 2015).…”

Section: Dense Image Matchingmentioning

confidence: 99%

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Accuracy of Measurements in Oblique Aerial Images for Urban Environment

Ostrowski

2016

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

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ABSTRACT:Oblique aerial images have been a source of data for urban areas for several years. However, the accuracy of measurements in oblique images during this time has been limited to a single meter due to the use of direct -georeferencing technology and the underlying digital elevation model. Therefore, oblique images have been used mostly for visualization purposes. This situation changed in recent years as new methods, which allowed for a higher accuracy of exterior orientation, were developed. Current developments include the process of determining exterior orientation and the previous but still crucial process of tie point extraction. Progress in this area was shown in the ISPRS/EUROSDR Benchmark on Multi-Platform Photogrammetry and is also noticeable in the growing interest in the use of this kind of imagery. The higher level of accuracy in the orientation of oblique aerial images that has become possible in the last few years should result in a higher level of accuracy in the measurements of these types of images.The main goal of this research was to set and empirically verify the accuracy of measurements in oblique aerial images. The research focused on photogrammetric measurements composed of many images, which use a high overlap within an oblique dataset and different view angles. During the experiments, two series of images of urban areas were used. Both were captured using five DigiCam cameras in a Maltese cross configuration. The tilt angles of the oblique cameras were 45 degrees, and the position of the cameras during flight used a high grade GPS/INS navigation system. The orientation of the images was set using the Pix4D Mapper Pro software with both measurements of the in-flight camera position and the ground control points (measured with GPS RTK technology). To control the accuracy, check points were used (which were also measured with GPS RTK technology).As reference data for the whole study, an area of the city-based map was used. The archived results were referred to image orientation accuracy and to the ground sampling distance of the used images. The results show that the recent development of image orientation methods for oblique aerial images allow these images to be used for high quality photogrammetric measurements.

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Section: Dense Image Matchingmentioning

confidence: 99%

“…A slightly different approach is presented by Nex et al (2013), whose research focused not on verification but on the extraction of building footprints. They utilized point clouds generated from oblique images using dense image matching in order to create a 2d vector building outline database.…”

Section: Introductionmentioning

confidence: 99%

Accuracy of Measurements in Oblique Aerial Images for Urban Environment

Ostrowski

2016

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

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“…Robust facade detection was done by utilizing horizontal and vertical facade texture together with height gradient from 3D points. Nex et al (2013) presented a methodology for the automated extraction of building footprints from photogrammetric point clouds. Points laying on walls with horizontal normal vectors were used to extract building boundaries, which can be bridged and smoothed to construct building footprints.…”

Section: Building Detection From Oblique Imagerymentioning

confidence: 99%

Feature Line Based Building Detection and Reconstruction From Oblique Airborne Imagery

Zhu

Jiang

Zhang

2015

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

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ABSTRACT:In this paper, a feature line based method for building detection and reconstruction from oblique airborne imagery is presented. With the development of Multi-View Stereo technology, increasing photogrammetric softwares are provided to generate textured meshes from oblique airborne imagery. However, errors in image matching and mesh segmentation lead to the low geometrical accuracy of building models, especially at building boundaries. To simplify massive meshes and construct accurate 3D building models, we integrate multi-view images and meshes by using feature lines, in which contour lines are used for building detection and straight skeleton for building reconstruction. Firstly, through the contour clustering method, buildings can be quickly and robustly detected from meshes. Then, a feature preserving mesh segmentation method is applied to accurately extract 3D straight skeleton from meshes. Finally, straight feature lines derived from multi-view images are used to rectify inaccurate parts of 3D straight skeleton of buildings. Therefore, low quality model can be refined by the accuracy improvement of mesh feature lines and rectification with feature lines of multi-view images. The test dataset in Zürich is provided by ISPRS/EuroSDR initiative Benchmark on High Density Image Matching for DSM Computation. The experiments reveal that the proposed method can obtain convincing and high quality 3D building models from oblique airborne imagery.

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“…Most frequently there are used integrated data -high resolution satellite photos and ALS point cloud (Wang et al, 2011;Cheng et al, 2008), as well as tristereoscopic satellite images (Bachofer & Hochschild, 2015) and oblique imaginery (Nex et al, 2013).…”

Section: Introductionmentioning

confidence: 99%