Authors:
Jaume Vergés-Llahí
1
;
Daniel Moldovan
2
and
Toshikazu Wada
3
Affiliations:
1
ATR Intelligent Robotics and Communication Laboratories, Japan
;
2
NICT Universal Media Center and ATR CIS Laboratories, Japan
;
3
Wakayama University, Japan
Keyword(s):
Epipolar geometry, reliability measure, essential matrix, camera-dependency graph.
Related
Ontology
Subjects/Areas/Topics:
Computational Geometry
;
Computer Vision, Visualization and Computer Graphics
;
Image Formation and Preprocessing
;
Multi-View Geometry
Abstract:
This paper presents a new technique to recover structure and motion from a large number of images acquired by an intrinsically calibrated perspective camera. We describe a method for computing reliable camera motion parameters that combines a camera–dependency graph, which describes the set of camera locations and the feasibility of pairwise motion calculations, and an algorithm for computing the weights on the edges of this graph. A new criterion for evaluating the reliability of the essential matrices thus produced with respect to the epipolar constraint is here introduced. It is composed of two main elements, namely, the uncertainty of the renormalization process by which the essential matrix is derived and the error between the estimated matrix and its decomposition into the motion parameters of translation and rotation. Experimental results show that there exists a clear correlation between the proposed reliability measure and the error in the estimation of such motion parameter
s. The performance of the proposed method is demonstrated on a sequence of short base-line images where it is made clear that the strategy based on the shortest paths in terms of unreliability provides remarkably superior results to those obtained from the paths of consecutive camera locations.
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