Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Scalable Recognition with a Vocabulary Tree
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
FAB-MAP: Probabilistic Localization and Mapping in the Space of Appearance
International Journal of Robotics Research
IEEE Transactions on Pattern Analysis and Machine Intelligence
Parallel Tracking and Mapping for Small AR Workspaces
ISMAR '07 Proceedings of the 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality
Video-rate localization in multiple maps for wearable augmented reality
ISWC '08 Proceedings of the 2008 12th IEEE International Symposium on Wearable Computers
Retrieving landmark and non-landmark images from community photo collections
Proceedings of the international conference on Multimedia
Location recognition using prioritized feature matching
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part II
Accurate image localization based on google maps street view
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part IV
City-scale landmark identification on mobile devices
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Discrete-continuous optimization for large-scale structure from motion
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Fast image-based localization using direct 2D-to-3D matching
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
Geometry directed browser for personal photographs
Proceedings of the Eighth Indian Conference on Computer Vision, Graphics and Image Processing
Hi-index | 0.00 |
We propose a powerful pipeline for determining the pose of a query image relative to a point cloud reconstruction of a large scene consisting of more than one million 3D points. The key component of our approach is an efficient and effective search method to establish matches between image features and scene points needed for pose estimation. Our main contribution is a framework for actively searching for additional matches, based on both 2D-to-3D and 3D-to-2D search. A unified formulation of search in both directions allows us to exploit the distinct advantages of both strategies, while avoiding their weaknesses. Due to active search, the resulting pipeline is able to close the gap in registration performance observed between efficient search methods and approaches that are allowed to run for multiple seconds, without sacrificing run-time efficiency. Our method achieves the best registration performance published so far on three standard benchmark datasets, with run-times comparable or superior to the fastest state-of-the-art methods.