論文

査読有り
2017年

Material Classification using Frequency- and Depth-Dependent Time-of-Flight Distortion

30TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2017)
  • Kenichiro Tanaka
  • ,
  • Yasuhiro Mukaigawa
  • ,
  • Takuya Funatomi
  • ,
  • Hiroyuki Kubo
  • ,
  • Yasuyuki Matsushita
  • ,
  • Yasushi Yagi

開始ページ
2740
終了ページ
2749
記述言語
英語
掲載種別
研究論文(国際会議プロシーディングス)
DOI
10.1109/CVPR.2017.293
出版者・発行元
IEEE

This paper presents a material classification method using an off-the-shelf Time-of-Flight (ToF) camera. We use a key observation that the depth measurement by a ToF camera is distorted in objects with certain materials, especially with translucent materials. We show that this distortion is caused by the variations of time domain impulse responses across materials and also by the measurement mechanism of the existing ToF cameras. Specifically, we reveal that the amount of distortion varies according to the modulation frequency of the ToF camera, the material of the object, and the distance between the camera and object. Our method uses the depth distortion of ToF measurements as features and achieves material classification of a scene. Effectiveness of the proposed method is demonstrated by numerical evaluation and real-world experiments, showing its capability of even classifying visually similar objects.

Web of Science ® 被引用回数 : 3

リンク情報
DOI
https://doi.org/10.1109/CVPR.2017.293
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000418371402085&DestApp=WOS_CPL

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