3D object recognition in cluttered environments by segment-based stereo vision

Yasushi Sumi, Yoshihiro Kawai, Takashi Yoshimi, Fumiaki Tomita

研究成果: Article査読

70 被引用数 (Scopus)


We propose a new method for 3D object recognition which uses segment-based stereo vision. An object is identified in a cluttered environment and its position and orientation (6 dof) are determined accurately enabling a robot to pick up the object and manipulate it. The object can be of any shape (planar figures, polyhedra, free-form objects) and partially occluded by other objects. Segment-based stereo vision is employed for 3D sensing. Both CAD-based and sensor-based object modeling subsystems are available. Matching is performed by calculating candidates for the object position and orientation using local features, verifying each candidate, and improving the accuracy of the position and orientation by an iteration method. Several experimental results are presented to demonstrate the usefulness of the proposed method.

ジャーナルInternational Journal of Computer Vision
出版ステータスPublished - 2002 1 1

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

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