Title
Material Classification from Time-of-Flight Distortions.
Abstract
This paper presents a material classification method using an off-the-shelf Time-of-Flight (ToF) camera. The proposed method is built upon a key observation that the depth measurement by a ToF camera is distorted for objects with certain materials, especially with translucent materials. We show that this distortion is due to the variation of time domain impulse responses across materials and also due to the measurement mechanism of the ToF cameras. Specifically, we reveal that the amount of distortion varies according to the modulation frequency of the ToF camera, the object material, and the distance between the camera and object. Our method uses the depth distortion of ToF measurements as a feature for classification and achieves material classification of a scene. Effectiveness of the proposed method is demonstrated by numerical evaluations and real-world experiments, showing its capability of material classification, even for visually indistinguishable objects.
Year
DOI
Venue
2019
10.1109/TPAMI.2018.2869885
IEEE transactions on pattern analysis and machine intelligence
Keywords
Field
DocType
Image classification,Distortion measurement,Time-domain analysis,Optical distortion,Optical imaging,Frequency measurement
Time domain,Computer vision,Material classification,Computer science,Impulse (physics),Artificial intelligence,Frequency modulation,Time of flight,Measured depth,Distortion,Optical imaging
Journal
Volume
Issue
ISSN
41
12
1939-3539
Citations 
PageRank 
References 
0
0.34
19
Authors
6
Name
Order
Citations
PageRank
Kenichiro Tanaka1106.30
Yasuhiro Mukaigawa247853.31
Takuya Funatomi37424.62
Hiroyuki Kubo41110.03
Yasuyuki Matsushita52046113.32
Yasushi Yagi61752186.22