Paper Info
Title
The Generalized Relative Pose And Scale Problem: View-Graph Fusion Via 2d-2d Registration
Abstract
It is well-known that the relative pose problem can be generalized to non-central cameras. We present a further generalization, denoted the generalized relative pose and scale problem. It has surprising importance for classical problems such as solving similarity transformations for view-graph concatenation in hierarchical structure from motion and loop-closure in visual SLAM, both posed as a 2D-2D registration problem. The relative pose problem and all its generalizations constitute a family of similar symmetric eigenvalue problems, which allow us to compress data and find a geometrically meaningful solution by an efficient search in the space of rotations. While the derivation of a completely general closed-form solver appears intractable, we make use of a simple heuristic global energy minimization scheme based on local minimum suppression, returning outstanding performance in practically relevant scenarios. Efficiency and reliability of our algorithm are demonstrated on both simulated and real data, supporting our claim of superior performance with respect to both generalized 2D-3D and 3D-3D registration approaches. By directly employing image information, we avoid the common noise in point clouds occuring especially along the depth direction.
Year
Venue
Field
2016
2016 IEEE WINTER CONFERENCE ON APPLICATIONS OF COMPUTER VISION (WACV 2016)
Structure from motion,Computer vision,Mathematical optimization,Heuristic,Generalization,Computer science,Minification,Artificial intelligence,Concatenation,Solver,Simultaneous localization and mapping,Eigenvalues and eigenvectors
DocType
ISSN
Citations 
Conference
2472-6737
1
PageRank 
References 
Authors
0.35
0
3
Name
Order
Citations
PageRank
Laurent Kneip143632.31
Chris Sweeney21017.42
Richard I. Hartley39809986.81