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A new strategy for improving vision based tracking accuracy based on utilization of camera calibration information

Alzarok, Hamza, Fletcher, Simon and Longstaff, Andrew P. (2016) A new strategy for improving vision based tracking accuracy based on utilization of camera calibration information. In: The 22nd IEEE International Conference on Automation & Computing. ICAC (2016). IEEE, University of Essex, Colchester, UK, pp. 290-295. ISBN 978-1-8621813-1-1

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Abstract— Camera calibration is one of the essential
components of a vision based tracking system where the objective
is to extract three dimensional information from a set of two
dimensional frames. The information extracted from the
calibration process is significant for examining the accuracy of the
vision sensor, and thus further for estimating its effectiveness as a
tracking system in real applications. This paper introduces
another use for this information in which the proper location of
the camera can be predicted. Anew mathematical formula based
on utilizing the extracted calibration information was used for
finding the optimum location for the camera, which provides the
best detection accuracy. Moreover, the calibration information
was also used for selecting the proper image Denoising filter. The
results obtained proved the validity of the proposed formula in
finding the desired camera location where the smallest detection
errors can be produced. Also, results showed that the proper
selection of the filter parameters led to a considerable
enhancement in the overall accuracy of the camera, reducing the
overall detection error by 0.2 mm.

Item Type: Book Chapter
AuthorLongstaff, Andrew
Additional Information: Additional copies of this publication are available from Curran Associates, Inc. 57 Morehouse Lane Red Hook, NY 12571 USA +1 845 758 0400 +1 845 758 2633 (FAX) email:
Subjects: T Technology > TJ Mechanical engineering and machinery
T Technology > TS Manufactures
Schools: School of Computing and Engineering
School of Computing and Engineering > Centre for Precision Technologies > Engineering Control and Machine Performance Research Group
Related URLs:
Depositing User: Hamza Alzarok
Date Deposited: 22 Sep 2016 14:41
Last Modified: 27 Oct 2016 04:20


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