2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2016
DOI: 10.1109/cvpr.2016.381
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Material Classification Using Raw Time-of-Flight Measurements

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Cited by 49 publications
(40 citation statements)
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“…'UVA' letters were used for this 3D depth imaging. The edges of each letter are recognizable, which supports the possibility of using a demonstrated ToF sensor for object and material recognition applications [37][38][39][40] . The fast switching performance of the hetero-integrated devices also elicits great potential for a spacious mapping application, such as LiDAR, where high-resolution can be realized by fast pulse repetition rate.…”
Section: Hetero-integration Of Gan Hemts and Gaas Vcselsmentioning
confidence: 67%
“…'UVA' letters were used for this 3D depth imaging. The edges of each letter are recognizable, which supports the possibility of using a demonstrated ToF sensor for object and material recognition applications [37][38][39][40] . The fast switching performance of the hetero-integrated devices also elicits great potential for a spacious mapping application, such as LiDAR, where high-resolution can be realized by fast pulse repetition rate.…”
Section: Hetero-integration Of Gan Hemts and Gaas Vcselsmentioning
confidence: 67%
“…Material Recognition of Subsurface Scattering: The use of delay and exposure can yield fundamental new information about light scattering in materials, particularly subsurface scattering. Previous researchers have used time-of-flight measurements to achieve a similar result [28], [57]. Consider the delay profile for a given material.…”
Section: Results: Delay Profiles and Materials Recognitionmentioning
confidence: 99%
“…This aspect allows our method to overcome some of the critical practical limitations of the related imaging methods. The proposed method requires hardware (mostly consumer-grade electronics) that is far less expensive than that required for the TOF-based NLOS imaging [16,24,25,26,27,33,37,39,40], and the method is more robust than the memoryeffect based imaging techniques that have a limited field-ofview [11,21]. Moreover, a recent publication [31] also uses only ordinal digital cameras but would require very specific scene setup (an accidental occlusion) to obtain better performance.…”
Section: Related Workmentioning
confidence: 99%