Workshop at the European Conference on Computer Vision

ECCV 2014: Computer Vision - ECCV 2014 Workshops pp 238-254 | Cite as

Online 3D Reconstruction and 6-DoF Pose Estimation for RGB-D Sensors

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8925)

Abstract

In this paper, we propose an approach to Simultaneous Localization and Mapping (SLAM) for RGB-D sensors. Our system computes 6-DoF pose and sparse feature map of the environment. We propose a novel keyframe selection scheme based on the Fisher information, and new loop closing method that utilizes feature-to-landmark correspondences inspired by image-based localization. As a result, the system effectively mitigates drift that is frequently observed in visual odometry system. Our approach gives lowest relative pose error amongst any other approaches tested on public benchmark dataset. A set of 3D reconstruction results on publicly available RGB-D videos are presented.

Keywords

Simultaneous Localization and Mapping RGB-D SLAM 

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Supplementary material

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Seoul National UniversitySeoulKorea
  2. 2.Hanyang UniversitySeoulKorea

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