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Local Homography Estimation Using Keypoint Descriptors

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Analysis, Retrieval and Delivery of Multimedia Content

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 158))

Abstract

This chapter presents a novel learning-based approach to estimate local homography of points belong to a given surface and shows that it is more accurate than specific affine region detection methods. While others works attempt this by using iterative algorithms developed for template matching, our method introduces a direct estimation of the transformation. It performs the following steps. First, a training set of features captures geometry and appearance information about keypoints taken from multiple views of the surface. Then incoming keypoints are matched against the training set in order to retrieve a cluster of features representing their identity. Finally the retrieved clusters are used to estimate the local homography of the regions around keypoints. Thanks to the high accuracy, outliers and bad estimates are filtered out by multiscale Summed Square Difference (SSD) test.

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Acknowledgments

This work is partially supported by the EU IST VidiVideo Project (Contract FP6-045547) and IM3I Project (Contract FP7-222267).

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Authors and Affiliations

  1. Media Integration and Communication Center (MICC), University of Florence, Florence, Italy

    Alberto Del Bimbo, Fernando Franco & Federico Pernici

Authors
  1. Alberto Del Bimbo
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  2. Fernando Franco
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  3. Federico Pernici
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Corresponding author

Correspondence to Federico Pernici .

Editor information

Editors and Affiliations

  1. , DEA - Facoltà di Ingegneria, University of Brescia, Studio N. 5, Via Branze 38, Brescia, 25123, Italy

    Nicola Adami

  2. , Elec. Engineering and Computer Science, Queen Mary University of London, Mile End Road, London, E1 4NS, United Kingdom

    Andrea Cavallaro

  3. , DII - Facoltà di Ingegneria, University of Brescia, Office N.7, Via Branze 38, Brescia, 25123, Italy

    Riccardo Leonardi

  4. , Department of Information Engineering, University of Brescia, Via Branze, 38, Brescia, 25123, Italy

    Pierangelo Migliorati

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Bimbo, A.D., Franco, F., Pernici, F. (2013). Local Homography Estimation Using Keypoint Descriptors. In: Adami, N., Cavallaro, A., Leonardi, R., Migliorati, P. (eds) Analysis, Retrieval and Delivery of Multimedia Content. Lecture Notes in Electrical Engineering, vol 158. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3831-1_12

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  • DOI: https://doi.org/10.1007/978-1-4614-3831-1_12

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  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4614-3830-4

  • Online ISBN: 978-1-4614-3831-1

  • eBook Packages: EngineeringEngineering (R0)

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