Image based detection of geometric changes in large scale urban evironments
| Aparna Taneja ETH Zurich |
Luca Ballan ETH Zurich |
Marc Pollefeys ETH Zurich |
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Abstract
We present an algorithm to detect changes in the geometry of an urban environment using some images observing its current state. The proposed method can be used to significantly optimize the process of updating the 3D model of a city changing over time, by restricting this process to only those areas where changes are detected.
With this application in mind, we designed our algorithm to specifically detect only structural changes in the environment, ignoring any changes in its appearance, and ignoring also all the changes which are not relevant for update purposes, such as cars, people etc. The method also accounts for all the challenges involved in a large scale application of change detection, such as, inaccuracies in the input geometry, errors in the geo-location data of the images, as well as, the limited amount of information due to sparse imagery.
Datasets
Small-scale datasets [Readme] (BMVC 2012)
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Structure | [ZIP] |
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Speedcam | [ZIP] |
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Residential | [ZIP] |
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Ticketbooth | [ZIP] |
Large-scale dataset
Related works
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City-Scale Change Detection in Cadastral 3D Models using Images Aparna Taneja, Luca Ballan, Marc Pollefeys CVPR 2013 [PDF] [Bib Tex] [Video] |
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Registration of Spherical Panoramic Images with Cadastral 3D Models Aparna Taneja, Luca Ballan, Marc Pollefeys 3DIMPVT 2012 [PDF] [Bib Tex] [Video] |
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Image based detection of geometric changes in urban evironments Aparna Taneja, Luca Ballan, Marc Pollefeys ICCV 2011 (oral) [PDF] [Bib Tex] [Video] [Talk] |
Acknowledgments:
The research leading to these results has received funding from the ERC under the EC’s Seventh Framework Programme (FP7/2007-2013) / ERC grant #210806, Swiss National Science Foundation, Honda and Google.