JOURNAL ARTICLE

Refining Outdoor Photometric Stereo Based on Sky Model

Kenji InoseShota ShimizuRei KawakamiYasuhiro MukaigawaKatsushi Ikeuchi

Year: 2013 Journal:   IPSJ Transactions on Computer Vision and Applications Vol: 5 (0)Pages: 104-108   Publisher: Springer Science+Business Media

Abstract

We propose an outdoor photometric stereo method, which considers environmental lighting for improving the performance of surface normal estimation. In the previous methods, the sky illumination effect has been either assumed to be constant throughout the scene, or to be removed by pre-processing. This paper exploits a sky model which can derive the entire sky luminance from a sky zenith image; then, sky illumination effect on a surface can be correctly calculated by iteratively refining its normal direction. This paper also extends a two-source photometric stereo method by introducing RANSAC, so that the input images of this method can be taken in a day. Experimental results with real outdoor objects show the effectiveness of the method.

Keywords:
Sky Computer science Computer vision Artificial intelligence RANSAC Zenith Remote sensing Luminance Photometry (optics) Image (mathematics) Geology Geography Stars Meteorology

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Citation History

Topics

Remote Sensing and LiDAR Applications
Physical Sciences →  Environmental Science →  Environmental Engineering
3D Surveying and Cultural Heritage
Physical Sciences →  Earth and Planetary Sciences →  Geology
Impact of Light on Environment and Health
Physical Sciences →  Environmental Science →  Global and Planetary Change
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