Type
Conference PaperAuthors
Su, ShuochenHeide, Felix
Swanson, Robin J.

Klein, Jonathan
Callenberg, Clara
Hullin, Matthias
Heidrich, Wolfgang

KAUST Department
Computer Science ProgramComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Visual Computing Center (VCC)
Date
2016-12-13Online Publication Date
2016-12-13Print Publication Date
2016-06Permanent link to this record
http://hdl.handle.net/10754/623865
Metadata
Show full item recordAbstract
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.Citation
Su 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.Sponsors
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.Additional Links
http://ieeexplore.ieee.org/document/7780750/ae974a485f413a2113503eed53cd6c53
10.1109/cvpr.2016.381