2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2016
DOI: 10.1109/cvpr.2016.381
|View full text |Cite
|
Sign up to set email alerts
|

Material Classification Using Raw Time-of-Flight Measurements

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

1
38
0

Year Published

2016
2016
2023
2023

Publication Types

Select...
7
1
1

Relationship

0
9

Authors

Journals

citations
Cited by 43 publications
(39 citation statements)
references
References 19 publications
1
38
0
Order By: Relevance
“…'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%