The generalized relative pose and scale problem: View-graph fusion via 2D-2D registration
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Authors
Kneip, Laurent
Sweeney, Chris
Hartley, Richard
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Publisher
IEEE
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.
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2016 IEEE Winter Conference on Applications of Computer Vision (WACV)
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Open Access