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Multi-view Point Cloud Registration Using Affine Shape Distributions

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Computer Vision -- ACCV 2014 (ACCV 2014)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9004))

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Abstract

Registration is crucial for the reconstruction of multi-view single plane illumination microscopy. By using fluorescent beads as fiduciary markers, this registration problem can be reduced to the problem of point clouds registration. We present a novel method for registering point clouds across views. This is based on a new local geometric descriptor - affine shape distribution - to represent the random spatial pattern of each point and its neighbourhood. To enhance its robustness and discriminative power against the missing data and outliers, a permutation and voting scheme based on affine shape distributions is developed to establish putative correspondence pairs across views. The underlying affine transformations are estimated based on the putative correspondence pairs via the random sample consensus. The proposed method is evaluated on three types of datasets including 3D random points, benchmark datasets and datasets from multi-view microscopy. Experiments show that the proposed method outperforms the state-of-the-arts when both point sets are contaminated by extremely large amount of outliers. Its robustness against the anisotropic z-stretching is also demonstrated in the registration of multi-view microscopy data.

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Authors and Affiliations

  1. Visual Computing Department, Institute for Infocomm Research, Singapore, Singapore

    Jia Du, Wei Xiong, Wenyu Chen, Jierong Cheng, Yue Wang, Ying Gu & Shue-Ching Chia

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  1. Jia Du
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  2. Wei Xiong
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  3. Wenyu Chen
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  4. Jierong Cheng
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  5. Yue Wang
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  6. Ying Gu
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  7. Shue-Ching Chia
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Correspondence to Jia Du .

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Editors and Affiliations

  1. Technische Universität München, Garching, Bayern, Germany

    Daniel Cremers

  2. University of Adelaide, Adelaide, South Australia, Australia

    Ian Reid

  3. Keio University, Yokohama, Kanagawa, Japan

    Hideo Saito

  4. University of California at Merced, Merced, California, USA

    Ming-Hsuan Yang

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Du, J. et al. (2015). Multi-view Point Cloud Registration Using Affine Shape Distributions. In: Cremers, D., Reid, I., Saito, H., Yang, MH. (eds) Computer Vision -- ACCV 2014. ACCV 2014. Lecture Notes in Computer Science(), vol 9004. Springer, Cham. https://doi.org/10.1007/978-3-319-16808-1_11

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  • DOI: https://doi.org/10.1007/978-3-319-16808-1_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-16807-4

  • Online ISBN: 978-3-319-16808-1

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