A fully automatic approach to register mobile mapping and airborne imagery to support the correction of platform trajectories in GNSS-denied urban areas

Jende, P.L.H.; Nex, Francesco; Gerke, M.; Vosselman, G.

doi:10.1016/j.isprsjprs.2018.04.017

Cited by 25 publications

(21 citation statements)

References 39 publications

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“…The method presented in this paper utilises oblique aerial imagery as a tertiary dataset. This can be regarded as a logical continuation of previous efforts, where aerial nadir images were used within the same context (Jende et al, 2018). Exclusively utilising aerial nadir images is limited to ground-based correspondences only, which has certain disadvantages with respect to the availability of correspondences and an adverse geometry within the adjustment solution.…”

mentioning

confidence: 89%

Co‐registration of panoramic mobile mapping images and oblique aerial images

Fanta-Jende

Nex

Vosselman

et al. 2019

The Photogrammetric Record

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Mobile mapping relies on satellite‐based positioning, which suffers from line‐of‐sight and multipath issues. As an alternative, this paper presents a fully automatic approach for the co‐registration of mobile mapping and oblique aerial images to introduce highly accurate and reliable ground control for mobile mapping data adjustment. An oblique view of a scene introduces similarities as well as challenges regarding co‐registration with mobile mapping images, which is supported by mutual planes in both datasets. Façade planes from a sparse point cloud are used as projection surfaces for the mobile mapping and aerial datasets, overcoming large perspective differences between them to simplify the registration. The performance of the procedure indicates an inlier rate of around 80%.

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mentioning

confidence: 89%

Co‐registration of panoramic mobile mapping images and oblique aerial images

Fanta-Jende

Nex

Vosselman

et al. 2019

The Photogrammetric Record

Self Cite

View full text Add to dashboard Cite

show abstract

“…The method presented in this chapter utilises oblique aerial imagery as a tertiary dataset. This can be regarded as a logical continuation of previous efforts, where aerial nadir images were used within the same context (Jende et al, 2018a). Exclusively utilising aerial nadir images is limited to groundbased correspondences only, which has certain disadvantages with respect to the availability of correspondences and an adverse geometry within the adjustment solution.…”

Section: Introductionmentioning

confidence: 89%

“…Similarly, in the authors' previous work, MM panoramic images were reprojected onto an artificial ground plane to achieve a higher resemblance to a vertical aerial (nadir) dataset (Jende et al, 2018a). The image registration problem can be constrained using guided matching strategies, as the absolute orientation (and thus the positioning error) is within an expected margin of error.…”

Section: Related Workmentioning

confidence: 99%

“…In our previous work (Jende et al, 2018a), we analysed the improvement of MM images compared to surveyed GCPs in three test areas using solely correspondences to aerial nadir images. Although a planimetric accuracy of up to 6 cm has been reached, in some case, an error in height has been introduced due to a very high altitude of the aerial platform (4500 metres).…”

Section: Related Workmentioning

confidence: 99%

“…With a very high inlier rate of more than 95%, this technique proved to be successful. For more information, please see Jende et al (2018a) or 'Chapter 3 Chapter 3 -A fully automatic approach to register mobile mapping and airborne imagery to support the correction of platform trajectories in GNSS-denied urban areas'.…”

Section: Co-registration Of Aerial Nadir and Mobile Mapping Imagesmentioning

confidence: 99%

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