Motion estimation for non-overlapping cameras by improvement of feature points matching based on urban 3D structure

Atsushi Kawasaki, Hideo Saito, Kosuke Hara

研究成果: Conference contribution

7 被引用数 (Scopus)

抄録

We propose a method of ego-motion estimation for a self-driving vehicle using multiple cameras. By finding corresponding points between the multi-camera images, we aim to enhance the accuracy of the ego-motion estimation. However since the viewing directions are very different from one camera to the other, a conventional algorithm such as SURF cannot detect a sufficient number of correspondences. We propose a novel matching algorithm by warping feature patches detected in different cameras based on urban 3D structure. We assume that detected features exist on the surface of buildings or roads and the patch around the feature is planar. Based on this assumption, we can warp the patches so that the feature descriptors are similar for the corresponding feature points. We apply Bundle Adjustment to the found correspondences to optimizes the odometry. The result shows higher estimation accuracy when compared to other matching method.

本文言語English
ホスト出版物のタイトルProceedings - International Conference on Image Processing, ICIP
出版社IEEE Computer Society
ページ1230-1234
ページ数5
2015-December
ISBN(印刷版)9781479983391
DOI
出版ステータスPublished - 2015 12月 9
イベントIEEE International Conference on Image Processing, ICIP 2015 - Quebec City, Canada
継続期間: 2015 9月 272015 9月 30

Other

OtherIEEE International Conference on Image Processing, ICIP 2015
国/地域Canada
CityQuebec City
Period15/9/2715/9/30

ASJC Scopus subject areas

  • 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
  • 信号処理

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