Accurate depth-map refinement by per-pixel plane fitting for stereo vision

Masashi Yokozuka, Kohji Tomita, Osamu Matsumoto, Atsuhiko Banno

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

This paper discusses the refinement of sparse and noisy depth-maps to improve stereo measurements. Our method functions as a post-filter for stereo measurements, to remove outliers and interpolate the depths of invalid pixels. Per-pixel plane fitting is employed to estimate the normals of an object's surface in a depth-map. These normals provide information regarding the interpolation of depth and the removal of outliers by evaluating the directions of surfaces. In our experiments, our method successfully reconstructed a dense and accurate geometry from a sparse and noisy depth-map, even where several dozen percent of pixels were outliers and only a few percent were from the original correct geometry. This result indicates a novel method of fast stereo measurement, because dense reconstruction can be performed without stereo matching for all pixels.

本文言語English
ホスト出版物のタイトル2016 23rd International Conference on Pattern Recognition, ICPR 2016
出版社Institute of Electrical and Electronics Engineers Inc.
ページ2807-2812
ページ数6
ISBN(電子版)9781509048472
DOI
出版ステータスPublished - 2016 1 1
外部発表はい
イベント23rd International Conference on Pattern Recognition, ICPR 2016 - Cancun, Mexico
継続期間: 2016 12 42016 12 8

出版物シリーズ

名前Proceedings - International Conference on Pattern Recognition
0
ISSN(印刷版)1051-4651

Other

Other23rd International Conference on Pattern Recognition, ICPR 2016
国/地域Mexico
CityCancun
Period16/12/416/12/8

ASJC Scopus subject areas

  • コンピュータ ビジョンおよびパターン認識

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