Material Classification Using Raw Time-of-Flight Measurements
Abstract
We propose a material classification method using raw time-of-flight (ToF) measurements. ToF cameras capture the correlation between a reference signal and the temporal response of material to incident illumination. Such measurements encode unique signatures of the material, i.e. the degree of subsurface scattering inside a volume. Subsequently, it offers an orthogonal domain of feature representation compared to conventional spatial and angular reflectance-based approaches. We demonstrate the effectiveness, robustness, and efficiency of our method through experiments and comparisons of real-world materials.
Cite
Text
Su et al. "Material Classification Using Raw Time-of-Flight Measurements." Conference on Computer Vision and Pattern Recognition, 2016. doi:10.1109/CVPR.2016.381Markdown
[Su et al. "Material Classification Using Raw Time-of-Flight Measurements." Conference on Computer Vision and Pattern Recognition, 2016.](https://mlanthology.org/cvpr/2016/su2016cvpr-material/) doi:10.1109/CVPR.2016.381BibTeX
@inproceedings{su2016cvpr-material,
title = {{Material Classification Using Raw Time-of-Flight Measurements}},
author = {Su, Shuochen and Heide, Felix and Swanson, Robin and Klein, Jonathan and Callenberg, Clara and Hullin, Matthias and Heidrich, Wolfgang},
booktitle = {Conference on Computer Vision and Pattern Recognition},
year = {2016},
doi = {10.1109/CVPR.2016.381},
url = {https://mlanthology.org/cvpr/2016/su2016cvpr-material/}
}