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.
|Title of host publication
|2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
|Institute of Electrical and Electronics Engineers (IEEE)
|Published - Dec 13 2016
Bibliographical noteKAUST Repository Item: Exported on 2020-10-01
Acknowledgements: This work was supported through the X-Rite Chair and Graduate School for Digital Material Appearance, the German Research Foundation, Grant HU 2273/2-1, the Baseline Funding of the King Abdullah University of Science and Technology, and a UBC 4 Year Fellowship.