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Robust Stereo-Vision Based 3D Object Reconstruction for the Assistive Robot FRIENDRISTIC-DURRANT, D. , GRIGORESCU, S. M. , GRASER, A. , COJBASIC, Z. , NIKOLIC, V.
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robust robot vision, feedback control in image processing, feature-based object recognition, neuro-fuzzy classification, assistive robot
vision(8), systems(8), object(7), robots(6), robotics(6), graeser(6), system(5), robot(5), autonomous(5), robotic(4)
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About this article
Date of Publication: 2011-11-30
Volume 11, Issue 4, Year 2011, On page(s): 15 - 22
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2011.04003
Web of Science Accession Number: 000297764500003
SCOPUS ID: 84856594148
A key requirement of assistive robot vision is the robust 3D object reconstruction in complex environments for reliable autonomous object manipulation. In this paper the idea is presented of achieving high robustness of a complete robot vision system against external influences such as variable illumination by including feedback control of the object segmentation in stereo images. The approach used is to change the segmentation parameters in closed-loop so that object features extraction is driven to a desired result. Reliable feature extraction is necessary to fully exploit a neuro-fuzzy classifier which is the core of the proposed 2D object recognition method, predecessor of 3D object reconstruction. Experimental results on the rehabilitation assistive robotic system FRIEND demonstrate the effectiveness of the proposed method.
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