Near-Field Photometric Stereo in Ambient Light

Fotios Logothetis, Roberto Mecca, Yvain Queau and Roberto Cipolla

Abstract

Shape recovery from shading information has recently regained importance due to the improvement towards making the Photometric Stereo technique more reliable in terms of appearance of reflective objects. However, although more advanced models have been lately proposed, 3D scanners based on this technology do not provide reliable reconstructions as long as the considered irradiance equation neglects any additive bias. Depending on the context, such bias assumes different physical meanings. For example, in murky water it is known as saturated backscattered effect or for acquisition in pure air medium it is known as ambient light. Although the theoretical part covers both cases, this work mostly focuses on the pure air acquisition case. Indeed, we present a new approach based on ratios of differences of images where an exhaustive set of physical features are tackled while dealing with Photometric Stereo acquisition with considerable importance for the ambient light. To the best of our knowledge, this is the first attempt to recover the shape from Photometric Stereo considering simultaneously perspective viewing geometry, non-linear light propagation, both specular and diffuse reflectance plus the additive bias of the ambient light. Proof of concept is provided by showing experimental results on synthetic and real data.

Session

Posters 1

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DOI

10.5244/C.30.61
https://dx.doi.org/10.5244/C.30.61

Citation

Fotios Logothetis, Roberto Mecca, Yvain Queau and Roberto Cipolla. Near-Field Photometric Stereo in Ambient Light. In Richard C. Wilson, Edwin R. Hancock and William A. P. Smith, editors, Proceedings of the British Machine Vision Conference (BMVC), pages 61.1-61.12. BMVA Press, September 2016.

Bibtex

        @inproceedings{BMVC2016_61,
        	title={Near-Field Photometric Stereo in Ambient Light},
        	author={Fotios Logothetis, Roberto Mecca, Yvain Queau and Roberto Cipolla},
        	year={2016},
        	month={September},
        	pages={61.1-61.12},
        	articleno={61},
        	numpages={12},
        	booktitle={Proceedings of the British Machine Vision Conference (BMVC)},
        	publisher={BMVA Press},
        	editor={Richard C. Wilson, Edwin R. Hancock and William A. P. Smith},
        	doi={10.5244/C.30.61},
        	isbn={1-901725-59-6},
        	url={https://dx.doi.org/10.5244/C.30.61}
        }