3D line segment based model generation by RGB-D camera for camera pose estimation

Yusuke Nakayama, Hideo Saito, Masayoshi Shimizu, Nobuyasu Yamaguchi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

In this paper, we propose a novel method for generating 3D line segment based model from an image sequence taken with a RGBD camera. Constructing 3D geometrical representation by 3D model is essential for model based camera pose estimation that can be performed by corresponding 2D features in images with 3D features of the captured scene. While point features are mostly used as such features for conventional camera pose estimation, we aim to use line segment features for improving the performance of the camera pose estimation. In this method, using RGB images and depth images of two continuous frames, 2D line segments from the current frame and 3D line segments from the previous frame are corresponded. The 2D-3D line segment correspondences provide camera pose of the current frame. All of 2D line segments are finally back projected to the world coordinate based on the estimated camera pose for generating 3D line segment based model of the target scene. In experiments, we confirmed that the proposed method can successfully generate line segment based models, while 3D models based on the point features often fail to successfully represent the target scene.

Original languageEnglish
Title of host publicationComputer Vision - 12th Asian Conference on Computer Vision, ACCV 2014, Revised Selected Papers
EditorsC.V. Jawahar, Shiguang Shan
PublisherSpringer Verlag
Pages459-472
Number of pages14
ISBN (Print)9783319166339
DOIs
Publication statusPublished - 2015
Event12th Asian Conference on Computer Vision, ACCV 2014 - Singapore, Singapore
Duration: 2014 Nov 12014 Nov 2

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9010
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other12th Asian Conference on Computer Vision, ACCV 2014
Country/TerritorySingapore
CitySingapore
Period14/11/114/11/2

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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