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CC BY-NC-ND V4.0, Open Access
Journal article
Cross domain 2D-3D descriptor matching for unconstrained 6-DOF pose estimation
Pattern recognition, Vol.142, 109655
2023
Abstract
This paper presents a novel approach for cross-domain descriptor matching between 2D and 3D modali-ties. The 2D-3D matching is applied to localize 2D images in 3D point clouds. Direct cross-domain match-ing allows our technique to localize images in any type of 3D point cloud without any constraints on the nature or mechanism by which it is obtained. We propose a learning based framework, called Desc-Matcher, to directly match features between the two modalities. A dataset of 2D and 3D features with corresponding locations in images and point clouds is generated to train the Desc-Matcher. To estimate the pose of an image in any 3D cloud, keypoints and feature descriptors are extracted from the query image and the point cloud. The trained Desc-Matcher is then used to match the features from the image and the point cloud. A robust pose estimator is used to predict the location and orientation of the query image from the corresponding positions of the matched 2D and 3D features. We carried out an extensive evaluation of the proposed method for indoor and outdoor scenarios and with different types of point clouds to verify the feasibility of our approach. Experimental results show that the proposed approach can reliably estimate the 6-DOF poses of query cameras in any type of 3D point cloud with high preci-sion. We achieved average median errors of 1. 09cm/ 0. 27 degrees and 19cm/ 0. 39 degrees on the Stanford and Cambridge datasets, respectively.
Details
- Title
- Cross domain 2D-3D descriptor matching for unconstrained 6-DOF pose estimation
- Authors/Creators
- Uzair Nadeem - Univ Western Australia, Dept Comp Sci & Software Engn, 35 Stirling Highway, Crawley, WA 6009, AustraliaMohammed Bennamoun - The University of Western AustraliaRoberto Togneri - The University of Western AustraliaFerdous Sohel - Murdoch University, Centre for Crop and Food InnovationAref Miri Rekavandi - Univ Western Australia, Dept Comp Sci & Software Engn, 35 Stirling Highway, Crawley, WA 6009, AustraliaFarid Boussaid - The University of Western Australia
- Publication Details
- Pattern recognition, Vol.142, 109655
- Publisher
- Elsevier Ltd.
- Number of pages
- 12
- Grant note
- DP210101682 / Australian Research Council SIRF scholarship from the University of Western Australia (UWA)
- Identifiers
- 991005593770007891
- Copyright
- © 2023 The Authors.
- Murdoch Affiliation
- School of Information Technology
- Language
- English
- Resource Type
- Journal article
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- Collaboration types
- Domestic collaboration
- Citation topics
- 4 Electrical Engineering, Electronics & Computer Science
- 4.116 Robotics
- 4.116.133 Simultaneous Localization and Mapping
- Web Of Science research areas
- Computer Science, Artificial Intelligence
- Engineering, Electrical & Electronic
- ESI research areas
- Engineering