Light fall-off stereo

Miao Liao; Liang Wang; Ruigang Yang; Minglun Gong

doi:10.1109/CVPR.2007.383159

Light fall-off stereo

Miao Liao, Liang Wang, Ruigang Yang, Minglun Gong

Computer Science

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

38 Scopus citations

Abstract

We present light fall-off stereo-LFS-a new method for computing depth from scenes beyond lambertian reflectance and texture. LFS takes a number of images from a stationary camera as the illumination source moves away from the scene. Based on the inverse square law for light intensity, the ratio images are directly related to scene depth from the perspective of the light source. Using this as the invariant, we developed both local and global methods for depth recovery. Compared to previous reconstruction methods for non-lamebrain scenes, LFS needs as few as two images, does not require calibrated camera or light sources, or reference objects in the scene. We demonstrated the effectiveness of LFS with a variety of real-world scenes.

Original language	English
Title of host publication	2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR'07
DOIs	https://doi.org/10.1109/CVPR.2007.383159
State	Published - 2007
Event	2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR'07 - Minneapolis, MN, United States Duration: Jun 17 2007 → Jun 22 2007

Publication series

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

Conference

Conference	2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR'07
Country/Territory	United States
City	Minneapolis, MN
Period	6/17/07 → 6/22/07

ASJC Scopus subject areas

Software
Computer Vision and Pattern Recognition

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10.1109/CVPR.2007.383159

Cite this

@inproceedings{fb0ae288d476401591b253bc4496215d,

title = "Light fall-off stereo",

abstract = "We present light fall-off stereo-LFS-a new method for computing depth from scenes beyond lambertian reflectance and texture. LFS takes a number of images from a stationary camera as the illumination source moves away from the scene. Based on the inverse square law for light intensity, the ratio images are directly related to scene depth from the perspective of the light source. Using this as the invariant, we developed both local and global methods for depth recovery. Compared to previous reconstruction methods for non-lamebrain scenes, LFS needs as few as two images, does not require calibrated camera or light sources, or reference objects in the scene. We demonstrated the effectiveness of LFS with a variety of real-world scenes.",

author = "Miao Liao and Liang Wang and Ruigang Yang and Minglun Gong",

year = "2007",

doi = "10.1109/CVPR.2007.383159",

language = "English",

isbn = "1424411807",

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

booktitle = "2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR'07",

note = "2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR'07 ; Conference date: 17-06-2007 Through 22-06-2007",

}

Liao, M, Wang, L, Yang, R & Gong, M 2007, Light fall-off stereo. in 2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR'07., 4270184, Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR'07, Minneapolis, MN, United States, 6/17/07. https://doi.org/10.1109/CVPR.2007.383159

Light fall-off stereo. / Liao, Miao; Wang, Liang; Yang, Ruigang et al.
2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR'07. 2007. 4270184 (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

TY - GEN

T1 - Light fall-off stereo

AU - Liao, Miao

AU - Wang, Liang

AU - Yang, Ruigang

AU - Gong, Minglun

PY - 2007

Y1 - 2007

N2 - We present light fall-off stereo-LFS-a new method for computing depth from scenes beyond lambertian reflectance and texture. LFS takes a number of images from a stationary camera as the illumination source moves away from the scene. Based on the inverse square law for light intensity, the ratio images are directly related to scene depth from the perspective of the light source. Using this as the invariant, we developed both local and global methods for depth recovery. Compared to previous reconstruction methods for non-lamebrain scenes, LFS needs as few as two images, does not require calibrated camera or light sources, or reference objects in the scene. We demonstrated the effectiveness of LFS with a variety of real-world scenes.

AB - We present light fall-off stereo-LFS-a new method for computing depth from scenes beyond lambertian reflectance and texture. LFS takes a number of images from a stationary camera as the illumination source moves away from the scene. Based on the inverse square law for light intensity, the ratio images are directly related to scene depth from the perspective of the light source. Using this as the invariant, we developed both local and global methods for depth recovery. Compared to previous reconstruction methods for non-lamebrain scenes, LFS needs as few as two images, does not require calibrated camera or light sources, or reference objects in the scene. We demonstrated the effectiveness of LFS with a variety of real-world scenes.

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U2 - 10.1109/CVPR.2007.383159

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M3 - Conference contribution

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SN - 9781424411801

T3 - Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

BT - 2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR'07

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Y2 - 17 June 2007 through 22 June 2007

ER -

Light fall-off stereo

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