Coupling ground-level panoramas and aerial imagery for change detection

Large-scale events represent a special challenge for crisis management. To ensure that participants can enjoy an event safely and carefree, it must be comprehensively prepared and attentively monitored. Remote sensing can provide valuable information to identify potential risks and take appropriate measures in order to prevent a disaster, or initiate emergency aid measures as quickly as possible in the event of an emergency. Especially, three-dimensional (3D) information that is derived using photogrammetry can be used to analyze the terrain and map existing structures that are set up at short notice. Using aerial imagery acquired during a German music festival in 2016 and the celebration of the German Protestant Church Assembly of 2017, the authors compare two-dimensional (2D) and novel fusion-based 3D change detection methods, and discuss their suitability for supporting large-scale events during the relevant phases of crisis management. This study serves to find out what added value the use of 3D change information can provide for on-site crisis management. Based on the results, an operational, fully automatic processor for crisis management operations and corresponding products for end users can be developed.

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3D exploitation of 2D ground-level & aerial imagery

2011 IEEE Applied Imagery Pattern Recognition Workshop (AIPR) ◽

10.1109/aipr.2011.6176363 ◽

2011 ◽

Cited By ~ 2

Author(s):

Peter Cho ◽

Noah Snavely

Keyword(s):

Ground Level ◽

Aerial Imagery

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Predicting Ground-Level Scene Layout from Aerial Imagery

2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) ◽

10.1109/cvpr.2017.440 ◽

2017 ◽

Cited By ~ 27

Author(s):

Menghua Zhai ◽

Zachary Bessinger ◽

Scott Workman ◽

Nathan Jacobs

Keyword(s):

Ground Level ◽

Aerial Imagery

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Methodology Development on Building Recognition and Change Detection Using Aerial Imagery

Journal of the Japan society of photogrammetry and remote sensing ◽

10.4287/jsprs.58.108 ◽

2019 ◽

Vol 58 (3) ◽

pp. 108-122

Author(s):

Lin ZHU ◽

Hideki SHIMAMURA

Keyword(s):

Change Detection ◽

Aerial Imagery ◽

Methodology Development ◽

Building Recognition

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SINGULARITY-FREE BUNDLE ADJUSTMENT

ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-annals-v-2-2020-43-2020 ◽

2020 ◽

Vol V-2-2020 ◽

pp. 43-48

Author(s):

E. Garcia

Keyword(s):

Initial Conditions ◽

Error Function ◽

Ground Level ◽

Bundle Adjustment ◽

Aerial Imagery ◽

Adjustment Process ◽

Reprojection Error ◽

Motion Problem ◽

The Cost ◽

Orientation Structure

Abstract. The photogrammetric bundle adjustment is well-behaved in the case of structured aerial imagery looking in the nadir direction. That is less so in the case of ground-level imagery with less structure and potentially looking in any direction. Besides, the cost function based on reprojection errors of tie points is not defined everywhere and exhibits singularities which renders this bundle adjustment process sensitive to initial conditions and outliers. In order to handle difficult configurations without incurring the risks posed by the reprojection function, we propose a new error function that is equivalent to the reprojection error when this error tends to zero, and that enjoys many desirables properties, such as being defined everywhere and being continuous. This allows an easier implementation of a robust bundle adjustment, and incidentally it also allows to solve derivative problems such as triangulating points starting from arbitrary initial positions, or estimating the relative positions of calibrated and oriented cameras starting from arbitrary positions, thus offering a simple solution to the known-orientation structure-from-motion problem.

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