Transparent Object Reconstruction via Coded Transport of Intensity

Chenguang Ma, Xing Lin, Jinli Suo, Qionghai Dai, Gordon Wetzstein

CVPR 2014

doi:10.1109/CVPR.2014.420 /cvpr/2014/ma2014cvpr-transparent/

Abstract

Capturing and understanding visual signals is one of the core interests of computer vision. Much progress has been made w.r.t. many aspects of imaging, but the reconstruction of refractive phenomena, such as turbulence, gas and heat flows, liquids, or transparent solids, has remained a challenging problem. In this paper, we derive an intuitive formulation of light transport in refractive media using light fields and the transport of intensity equation. We show how coded illumination in combination with pairs of recorded images allow for robust computational reconstruction of dynamic two and three-dimensional refractive phenomena.

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Cite

Text

Ma et al. "Transparent Object Reconstruction via Coded Transport of Intensity." Conference on Computer Vision and Pattern Recognition, 2014. doi:10.1109/CVPR.2014.420

Markdown

[Ma et al. "Transparent Object Reconstruction via Coded Transport of Intensity." Conference on Computer Vision and Pattern Recognition, 2014.](https://mlanthology.org/cvpr/2014/ma2014cvpr-transparent/) doi:10.1109/CVPR.2014.420

BibTeX

@inproceedings{ma2014cvpr-transparent,
  title     = {{Transparent Object Reconstruction via Coded Transport of Intensity}},
  author    = {Ma, Chenguang and Lin, Xing and Suo, Jinli and Dai, Qionghai and Wetzstein, Gordon},
  booktitle = {Conference on Computer Vision and Pattern Recognition},
  year      = {2014},
  doi       = {10.1109/CVPR.2014.420},
  url       = {https://mlanthology.org/cvpr/2014/ma2014cvpr-transparent/}
}