TransCut: Transparent object segmentation from a light-field image

Yichao Xu, Hajime Nagahara, Atsushi Shimada, Rin Ichiro Taniguchi

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

27 被引用数 (Scopus)

抄録

The segmentation of transparent objects can be very useful in computer vision applications. However, because they borrow texture from their background and have a similar appearance to their surroundings, transparent objects are not handled well by regular image segmentation methods. We propose a method that overcomes these problems using the consistency and distortion properties of a light-field image. Graph-cut optimization is applied for the pixel labeling problem. The light-field linearity is used to estimate the likelihood of a pixel belonging to the transparent object or Lambertian background, and the occlusion detector is used to find the occlusion boundary. We acquire a light field dataset for the transparent object, and use this dataset to evaluate our method. The results demonstrate that the proposed method successfully segments transparent objects from the background.

本文言語英語
ホスト出版物のタイトル2015 International Conference on Computer Vision, ICCV 2015
出版社Institute of Electrical and Electronics Engineers Inc.
ページ3442-3450
ページ数9
ISBN(電子版)9781467383912
DOI
出版ステータス出版済み - 2 17 2015
イベント15th IEEE International Conference on Computer Vision, ICCV 2015 - Santiago, チリ
継続期間: 12 11 201512 18 2015

出版物シリーズ

名前Proceedings of the IEEE International Conference on Computer Vision
2015 International Conference on Computer Vision, ICCV 2015
ISSN(印刷版)1550-5499

その他

その他15th IEEE International Conference on Computer Vision, ICCV 2015
国/地域チリ
CitySantiago
Period12/11/1512/18/15

All Science Journal Classification (ASJC) codes

  • ソフトウェア
  • コンピュータ ビジョンおよびパターン認識

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