Swanson, Robin J.
KAUST DepartmentVisual Computing Center (VCC)
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Computer Science Program
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AbstractWe 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.
CitationSu S, Heide F, Swanson R, Klein J, Callenberg C, et al. (2016) Material Classification Using Raw Time-of-Flight Measurements. 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Available: http://dx.doi.org/10.1109/cvpr.2016.381.
SponsorsThis 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.