On a cyclic string-to-string correction problem
Information Processing Letters
Linear Multi View Reconstruction and Camera Recovery Using a Reference Plane
International Journal of Computer Vision
Automatic Camera Recovery for Closed or Open Image Sequences
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
Multi-view Matching for Unordered Image Sets, or "How Do I Organize My Holiday Snaps?"
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Learning Intrinsic Video Content Using Levenshtein Distance in Graph Partitioning
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Baseline Detection and Localization for Invisible Omnidirectional Cameras
International Journal of Computer Vision - Special Issue on Omni-Directional Research in Japan
Visual Modeling with a Hand-Held Camera
International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Levenshtein Distance for Graph Spectral Features
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Translation Estimation from Omnidirectional Images
DICTA '05 Proceedings of the Digital Image Computing on Techniques and Applications
A Comparison of Affine Region Detectors
International Journal of Computer Vision
Structure from Motion with Wide Circular Field of View Cameras
IEEE Transactions on Pattern Analysis and Machine Intelligence
Photo tourism: exploring photo collections in 3D
ACM SIGGRAPH 2006 Papers
MonoSLAM: Real-Time Single Camera SLAM
IEEE Transactions on Pattern Analysis and Machine Intelligence
Vision-Based SLAM: Stereo and Monocular Approaches
International Journal of Computer Vision
Monocular Vision for Mobile Robot Localization and Autonomous Navigation
International Journal of Computer Vision
SBA: A software package for generic sparse bundle adjustment
ACM Transactions on Mathematical Software (TOMS)
Self-calibration of hybrid central catadioptric and perspective cameras
Computer Vision and Image Understanding
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There is currently an abundance of vision algorithms which, provided with a sequence of images that have been acquired from sufficiently close successive 3D locations, are capable of determining the relative positions of the viewpoints from which the images have been captured. However, very few of these algorithms can cope with unordered image sets. This paper presents an efficient method for recovering the position and orientation parameters corresponding to the viewpoints of a set of panoramic images for which no a priori order information is available, along with certain structure information regarding the imaged environment. The proposed approach assumes that all images have been acquired from a constant height above a planar ground and operates sequentially, employing the Levenshtein distance to deduce the spatial proximity of image viewpoints and thus determine the order in which images should be processed. The Levenshtein distance also provides matches between imaged points, from which their corresponding environment points can be reconstructed. Image matching with the aid of the Levenshtein distance forms the crux of an iterative process that alternates between image localization from multiple reconstructed points and point reconstruction from multiple image projections, until all views have been localized. Periodic refinement of the reconstruction with the aid of bundle adjustment, distributes the reconstruction error among images. The approach is demonstrated on several unordered sets of panoramic images obtained in indoor environments.