Camera pose estimation by an artificial neural network

Authors:
Ryan G. Benton;Chee-hung Henry Chu
Affiliations:
Center for Advanced Computer Studies, The University of Louisiana at Lafayette, Lafayette, LA,;Center for Advanced Computer Studies, The University of Louisiana at Lafayette, Lafayette, LA
Venue:
ICONIP'06 Proceedings of the 13th international conference on Neural Information Processing - Volume Part II
Year:
2006

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Abstract

Reconstruction of a three-dimensional scene using images taken from two views is possible if the relative pose of the cameras is known. A traditional approach to estimating the pose of the cameras uses eight pairs of corresponding points and involves the solution of a set of homogeneous equations. We propose a multi-layered feedforward network solution. Empirical results demonstrate the feasibility of using the network to recover the relative pose of the cameras in the three-dimensional world.