Efficient & Effective Prioritized Matching for Large-Scale Image-Based Localization
ETH Zurich · RWTH Aachen University
Abstract
Accurately determining the position and orientation from which an image was taken, i.e., computing the camera pose, is a fundamental step in many Computer Vision applications. The pose can be recovered from 2D-3D matches between 2D image positions and points in a 3D model of the scene. Recent advances in Structure-from-Motion allow us to reconstruct large scenes and thus create the need for image-based localization methods that efficiently handle large-scale 3D models while still being effective, i.e., while localizing as many images as possible. This paper presents an approach for large scale image-based localization that is both efficient and effective. At the core of our approach is a novel prioritized…
Citation impact
- FWCI
- 767.10
- Percentile
- 100%
- References
- 52
Authors
3Topics & keywords
- Artificial intelligence
- Computer science
- Computer vision
- Visibility
- Quantization (signal processing)
- Matching (statistics)
- Process (computing)
- Orientation (vector space)