Document Detail


Hand-eye and radial distortion calibration for rigid endoscopes.
MedLine Citation:
PMID:  23303645     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
BACKGROUND: In this paper, we propose a non-linear calibration method for hand-eye system equipped with a camera undergoing radial distortion as the rigid endoscope. Whereas classic methods propose either a separated estimation of the camera intrinsics and the hand-eye transform or a mixed non-linear estimation of both hand-eye and camera intrinsics assuming a pin-hole model, the proposed approach enables a simultaneous refinement of the hand-eye and the camera parameters including the distortion factor with only three frames of the calibrated pattern. METHODS: Our approach relies on three steps: (i) linear initial estimates of hand-eye and radial distortion with minimum number of frames: one single image to estimate the radial distortion and three frames to estimate the initial hand-eye transform, (ii) we propose to express the camera extrinsic with respect to hand-eye and world-grid transforms and (iii) we run bundle adjustment on the reprojection error with respect to the distortion parameters, the camera intrinsics and the hand-eye transform. RESULTS: Our method is quantitatively compared with state-of-the-art linear and non-linear methods. We show that our method provides a 3D reconstruction error of approximately 5% of the size of the 3D shape. CONCLUSIONS: Our experimental results show the effectiveness of simultaneously estimating hand-eye and distortion parameters for 3D reconstruction. Copyright © 2013 John Wiley & Sons, Ltd.
Authors:
Abed Malti; Joao Pedro Barreto
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2013-1-10
Journal Detail:
Title:  The international journal of medical robotics + computer assisted surgery : MRCAS     Volume:  -     ISSN:  1478-596X     ISO Abbreviation:  Int J Med Robot     Publication Date:  2013 Jan 
Date Detail:
Created Date:  2013-1-10     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101250764     Medline TA:  Int J Med Robot     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Copyright Information:
Copyright © 2013 John Wiley & Sons, Ltd.
Affiliation:
ALCoV-ISIT, UMR 6284 CNRS/Université d'Auvergne, Clermont-Ferrand, France.
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