Using cloud shadows to infer scene structure and camera calibration

Nathan Jacobs; Brian Bies; Robert Pless

doi:10.1109/CVPR.2010.5540093

Using cloud shadows to infer scene structure and camera calibration

Nathan Jacobs, Brian Bies, Robert Pless

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

19 Scopus citations

Abstract

We explore the use of clouds as a form of structured lighting to capture the 3D structure of outdoor scenes observed over time from a static camera. We derive two cues that relate 3D distances to changes in pixel intensity due to clouds shadows. The first cue is primarily spatial, works with low frame-rate time lapses, and supports estimating focal length and scene structure, up to a scale ambiguity. The second cue depends on cloud motion and has a more complex, but still linear, ambiguity. We describe a method that uses the spatial cue to estimate a depth map and a method that combines both cues. Results on time lapses of several outdoor scenes show that these cues enable estimating scene geometry and camera focal length.

Original language	English
Title of host publication	2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010
Pages	1102-1109
Number of pages	8
DOIs	https://doi.org/10.1109/CVPR.2010.5540093
State	Published - 2010
Event	2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010 - San Francisco, CA, United States Duration: Jun 13 2010 → Jun 18 2010

Publication series

Name	Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
ISSN (Print)	1063-6919

Conference

Conference	2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010
Country/Territory	United States
City	San Francisco, CA
Period	6/13/10 → 6/18/10

ASJC Scopus subject areas

Software
Computer Vision and Pattern Recognition

Access to Document

10.1109/CVPR.2010.5540093

Cite this

Jacobs, N., Bies, B., & Pless, R. (2010). Using cloud shadows to infer scene structure and camera calibration. In 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010 (pp. 1102-1109). Article 5540093 (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition). https://doi.org/10.1109/CVPR.2010.5540093

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title = "Using cloud shadows to infer scene structure and camera calibration",

abstract = "We explore the use of clouds as a form of structured lighting to capture the 3D structure of outdoor scenes observed over time from a static camera. We derive two cues that relate 3D distances to changes in pixel intensity due to clouds shadows. The first cue is primarily spatial, works with low frame-rate time lapses, and supports estimating focal length and scene structure, up to a scale ambiguity. The second cue depends on cloud motion and has a more complex, but still linear, ambiguity. We describe a method that uses the spatial cue to estimate a depth map and a method that combines both cues. Results on time lapses of several outdoor scenes show that these cues enable estimating scene geometry and camera focal length.",

author = "Nathan Jacobs and Brian Bies and Robert Pless",

year = "2010",

doi = "10.1109/CVPR.2010.5540093",

language = "English",

isbn = "9781424469840",

series = "Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition",

pages = "1102--1109",

booktitle = "2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010",

note = "2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010 ; Conference date: 13-06-2010 Through 18-06-2010",

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Jacobs, N, Bies, B & Pless, R 2010, Using cloud shadows to infer scene structure and camera calibration. in 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010., 5540093, Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 1102-1109, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010, San Francisco, CA, United States, 6/13/10. https://doi.org/10.1109/CVPR.2010.5540093

Using cloud shadows to infer scene structure and camera calibration. / Jacobs, Nathan; Bies, Brian; Pless, Robert.
2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010. 2010. p. 1102-1109 5540093 (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Bies, Brian

AU - Pless, Robert

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N2 - We explore the use of clouds as a form of structured lighting to capture the 3D structure of outdoor scenes observed over time from a static camera. We derive two cues that relate 3D distances to changes in pixel intensity due to clouds shadows. The first cue is primarily spatial, works with low frame-rate time lapses, and supports estimating focal length and scene structure, up to a scale ambiguity. The second cue depends on cloud motion and has a more complex, but still linear, ambiguity. We describe a method that uses the spatial cue to estimate a depth map and a method that combines both cues. Results on time lapses of several outdoor scenes show that these cues enable estimating scene geometry and camera focal length.

AB - We explore the use of clouds as a form of structured lighting to capture the 3D structure of outdoor scenes observed over time from a static camera. We derive two cues that relate 3D distances to changes in pixel intensity due to clouds shadows. The first cue is primarily spatial, works with low frame-rate time lapses, and supports estimating focal length and scene structure, up to a scale ambiguity. The second cue depends on cloud motion and has a more complex, but still linear, ambiguity. We describe a method that uses the spatial cue to estimate a depth map and a method that combines both cues. Results on time lapses of several outdoor scenes show that these cues enable estimating scene geometry and camera focal length.

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Using cloud shadows to infer scene structure and camera calibration

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ASJC Scopus subject areas

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