Literature DB >> 34971528

A Pose-only Solution to Visual Reconstruction and Navigation.

Qi Cai, Lilian Zhang, Yuanxin Wu, Wenxian Yu, Dewen Hu.   

Abstract

Visual navigation and three-dimensional (3D) scene reconstruction are essential for robotics to interact with the surrounding environment. Large-scale scenarios and computational robustness are great challenges facing the research community to achieve this goal. This paper raised a pose-only imaging geometry representation and algorithms that might help solve these challenges. The pose-only representation, equivalent to the classical multiple-view geometry, is discovered to be linearly related to camera global translations, which allows for efficient and robust camera motion estimation. As a result, the spatial feature coordinates can be analytically reconstructed and do not require nonlinear optimization. Comprehensive experiments demonstrate that the computational efficiency of recovering the scene and associated camera poses is significantly improved by 2-4 orders of magnitude.

Entities:  

Year:  2021        PMID: 34971528     DOI: 10.1109/TPAMI.2021.3139681

Source DB:  PubMed          Journal:  IEEE Trans Pattern Anal Mach Intell        ISSN: 0098-5589            Impact factor:   6.226


  1 in total

1.  Development and evaluation of a double-check support system using artificial intelligence in endoscopic screening for gastric cancer.

Authors:  Hirotaka Oura; Tomoaki Matsumura; Mai Fujie; Tsubasa Ishikawa; Ariki Nagashima; Wataru Shiratori; Mamoru Tokunaga; Tatsuya Kaneko; Yushi Imai; Tsubasa Oike; Yuya Yokoyama; Naoki Akizue; Yuki Ota; Kenichiro Okimoto; Makoto Arai; Yuki Nakagawa; Mari Inada; Kazuya Yamaguchi; Jun Kato; Naoya Kato
Journal:  Gastric Cancer       Date:  2021-10-15       Impact factor: 7.370

  1 in total

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