Refining Geometry from Depth Sensors using IR Shading Images-Reference-Cited by-同舟云学术

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Refining Geometry from Depth Sensors using IR Shading Images

Published:2016-09-19 Issue:1 Volume:122 Page:1-16
ISSN:0920-5691
Container-title:International Journal of Computer Vision
language:en
Short-container-title:Int J Comput Vis

Author:

Choe Gyeongmin,Park Jaesik,Tai Yu-Wing,Kweon In So

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Link

http://link.springer.com/content/pdf/10.1007/s11263-016-0937-y.pdf

Reference50 articles.

1. Bellia, L., Bisegna, F., & Spada, G. (2011). Lighting in indoor environments: Visual and non-visual effects of light sources with different spectral power distributions. Building and Environment, 46(10), 1984–1992.

2. Besl, P., & McKay, N. D. (1992). A method for registration of 3-d shapes. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 14(2), 239–256.

3. Bohme, M., Haker, M., Martinetz, T., & Barth, E. (2010). Shading constraint improves accuracy of time-of-flight measurements. Computer Vision and Image Understanding (CVIU), 114(12), 1329–1335.

4. Boykov, Y., & Kolmogorov, V. (2004). An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 26(9), 1124–1137.

5. Choe, G., Narasimhan, S. G., & Kweon, I. S. (2016). Simultaneous estimation of near IR BRDF and fine-scale surface geometry. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 2452–2460).

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