Material Classification Using Raw Time-of-Flight Measurements

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.

@Article{Su2016_tof_classification,
	author   = {Su, Shuochen and Heide, Felix and Swanson, Robin and Klein, Jonathan and Callenberg, Clara and Hullin, Matthias B. and Heidrich, Wolfgang},
	journal  = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
	title    = {Material Classification Using Raw Time-of-Flight Measurements},
	year     = {2016},
	month    = {12}
}