Video-Based Camera Localization Using Anchor View Detection and Recursive 3D Reconstruction
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Abstract (arXiv)
In this paper we introduce a new camera localization strategy designed for image sequences captured in challenging industrial situations such as industrial parts inspection. To deal with peculiar appearances that hurt standard 3D reconstruction pipeline, we exploit pre-knowledge of the scene by selecting key frames in the sequence (called as anchors) which are roughly connected to a certain location. Our method then seek the location of each frame in time-order, while recursively updating an augmented 3D model which can provide current camera location and surrounding 3D structure. In an experiment on a practical industrial situation, our method can localize over 99% frames in the input sequence, whereas standard localization methods fail to reconstruct a complete camera trajectory.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 8 of its 31 references that are in the map. First posted on arXiv 7 Jul 2021.
Builds on
8 of 31 references.
References · 8
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- 2015NetVLAD: CNN architecture for weakly supervised place recognitioncited by 935
- 2016Past, Present, and Future of Simultaneous Localization And Mapping: Towards the Robust-Perception Agecited by 405
- 2019OpenVSLAM: A Versatile Visual SLAM Frameworkcited by 64
- 2018Scale Estimation of Monocular SfM for a Multi-modal Stereo Cameracited by 2
- 20203D Pipe Network Reconstruction Based on Structure from Motion with Incremental Conic Shape Detection and Cylindrical Constraintcited by 2
- 2021VIO-Aided Structure from Motion Under Challenging Environmentscited by 2
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Citing papers per year: 2022: 1.
1 paper.