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Conference Towards Autonomous Robotic Systems

TAROS 2011: Towards Autonomous Robotic Systems pp 36–45Cite as

A Recursive Least Squares Solution for Recovering Robust Planar Homographies

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6856))

Abstract

Presented is a recursive least squares (RLS) solution for estimating planar homographies between overlapping images. The use of such a technique stems from its ability in dealing with corrupted and periodic measurements to provide the best solution. Furthermore, its capacity for providing reliable results for time varying parameter estimation also motivates its use in the context of real time cooperative image mosaicing where optimal transformation between mobile platforms is likely to change due to motion and varying ambient conditions and thus a way to tackle this problem real time is what is required. Additionally, and within the same context, a derived ”match making” algorithm is introduced based on high curvature points (Harris points) and 3D intensity histograms which are in-turn matched using the L 2 and L  ∞  and then compared to classical cross correlation(CC) techniques.

Experimental results show that for synthetic data heavily corrupted by noise the RLS does a decent job of finding an improved homography, provided that the initial estimate is good. Results from real image data show similar results where the homography estimate is improved upon by periodic measurements. The match making algorithm proposed fairs well compared to intensity vector techniques, with the L  ∞  based method coming out on top.

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Author information

Authors and Affiliations

  1. Cranfield Defence and Security, Department of Informatics and Systems Engineering, Sensors Group, Cranfield University, Shrivenham, UK

    Saad Ali Imran & Nabil Aouf

Authors
  1. Saad Ali Imran
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  2. Nabil Aouf
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Editor information

Editors and Affiliations

  1. Department of Automatic Control and Systems Engineering, The University of Sheffield, Mappin Street, S1 3JD, Sheffield, UK

    Roderich Groß

  2. Materials and Engineering Research Institute, Sheffield Hallam University, City Campus, Horward Street, S1 1WB, Sheffield, UK

    Lyuba Alboul  & Jacques Penders  & 

  3. Department of Computing, Engineering and Mathematical Sciences, Bristol Robotics Laboratory (BRL), University of Bristol and the West of England, Bristol Business Park, BS16 1QD, Bistol, UK

    Chris Melhuish

  4. Department of Electrical and Electronic Engineering, Imperial College London, Exhibition Road, SW7 2BT, London, UK

    Mark Witkowski

  5. Department of Psychology, The University of Sheffield, Wstern Bank, S10 2TN, Sheffield, UK

    Tony J. Prescott

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© 2011 Springer-Verlag Berlin Heidelberg

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Imran, S.A., Aouf, N. (2011). A Recursive Least Squares Solution for Recovering Robust Planar Homographies. In: Groß, R., Alboul, L., Melhuish, C., Witkowski, M., Prescott, T.J., Penders, J. (eds) Towards Autonomous Robotic Systems. TAROS 2011. Lecture Notes in Computer Science(), vol 6856. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23232-9_4

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  • DOI: https://doi.org/10.1007/978-3-642-23232-9_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23231-2

  • Online ISBN: 978-3-642-23232-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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