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Stereo Fusion Using a Refractive Medium on a Binocular Base

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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

The performance of depth reconstruction in binocular stereo relies on how adequate the predefined baseline for a target scene is. Wide-baseline stereo is capable of discriminating depth better than the narrow one, but it often suffers from spatial artifacts. Narrow-baseline stereo can provide a more elaborate depth map with less artifacts, while its depth resolution tends to be biased or coarse due to the short disparity. In this paper, we propose a novel optical design of heterogeneous stereo fusion on a binocular imaging system with a refractive medium, where the binocular stereo part operates as wide-baseline stereo; the refractive stereo module works as narrow-baseline stereo. We then introduce a stereo fusion workflow that combines the refractive and binocular stereo algorithms to estimate fine depth information through this fusion design. The quantitative and qualitative results validate the performance of our stereo fusion system in measuring depth, compared with homogeneous stereo approaches.

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Acknowledgement

Min H. Kim gratefully acknowledges Korea NRF grants (2013R1A1A1010165 and 2013M3A6A6073718) and additional support by Microsoft Research Asia and an ICT R&D program of MSIP/IITP (10041313).

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Authors and Affiliations

  1. KAIST, Daejeon, Korea

    Seung-Hwan Baek & Min H. Kim

Authors
  1. Seung-Hwan Baek
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  2. Min H. Kim
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Corresponding author

Correspondence to Min H. Kim .

Editor information

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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Baek, SH., Kim, M.H. (2015). Stereo Fusion Using a Refractive Medium on a Binocular Base. 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_34

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  • DOI: https://doi.org/10.1007/978-3-319-16808-1_34

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-16807-4

  • Online ISBN: 978-3-319-16808-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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