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On-the-fly adaptation of regression forests for online camera relocalisation

Abstract:

Camera relocalisation is an important problem in computer vision, with applications in simultaneous localisation and mapping, virtual/augmented reality and navigation. Common techniques either match the current image against keyframes with known poses coming from a tracker, or establish 2D-to-3D correspondences between keypoints in the current image and points in the scene in order to estimate the camera pose. Recently, regression forests have become a popular alternative to establish such co...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/CVPR.2017.31

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Institution:
University of Oxford
Oxford college:
Wolfson College
Role:
Author
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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
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Grant:
ERC-2012-AdG 321162-HELIOS
Publisher:
Institute for Electrical and Electronics Engineers Publisher's website
Journal:
2017 Conference on Computer Vision and Pattern Recognition Journal website
Host title:
2017 Conference on Computer Vision and Pattern Recognition (CVPR 2017)
Publication date:
2017-11-01
Acceptance date:
2017-03-03
DOI:
ISSN:
1063-6919
Source identifiers:
689001
Pubs id:
pubs:689001
UUID:
uuid:fafd9528-512e-4927-a1ad-dc104147fd92
Local pid:
pubs:689001
Deposit date:
2017-04-11

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