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Improved Stereo Vision of Indoor Dense Suspended Scatterers Scenes from De-scattering Images

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Advances in Visual Computing (ISVC 2016)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10072))

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Abstract

Stereo vision is important in robotics since retrieving depth is very necessary in many robotics applications. Most of state-of-the-art stereo vision algorithms solve the problem with clear images but not the images corrupted by scattering. In this paper, we propose the stereo vision system for robot working in dense suspended scatterers environment. The imaging model of images taken in the environment under active light source based on single scattering phenomenon is analyzed. Based on that, scattering signal can be removed from images. The recovered images are then used as input image for stereo vision. The proposed method is then evaluated based on quality of stereo depth map.

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Authors and Affiliations

  1. Department of Mechanical Engineering, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon, 34141, South Korea

    Chanh D. Tr. Nguyen, Kyung-Soo Kim & Soohyun Kim

  2. USRC, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon, 34141, South Korea

    Kyeong Yong Cho

  3. Equipment Engineering Lab., Korea Hydro & Nuclear Power Co., 70, 1312-gil, Yuseong-daero, Yuseong-gu, Daejeon, 34141, South Korea

    You Hyun Jang

Authors
  1. Chanh D. Tr. Nguyen
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  2. Kyeong Yong Cho
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  3. You Hyun Jang
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  4. Kyung-Soo Kim
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  5. Soohyun Kim
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Corresponding author

Correspondence to Soohyun Kim .

Editor information

Editors and Affiliations

  1. University of Nevada , Reno, Nevada, USA

    George Bebis

  2. NASA Ames Research Center , Moffett Field, California, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory , Berkeley, California, USA

    Bahram Parvin

  4. Desert Research Institute , Reno, Nevada, USA

    Darko Koracin

  5. The Australian National University , O'Malley, Aust Capital Terr, Australia

    Fatih Porikli

  6. Pilot AI Labs , Redwood City, California, USA

    Sandra Skaff

  7. University of Florida , Gainesville, Florida, USA

    Alireza Entezari

  8. Google Inc. , Mountain View, California, USA

    Jianyuan Min

  9. Osaka University , Osaka, Japan

    Daisuke Iwai

  10. The MOVES Institute , Monterey, California, USA

    Amela Sadagic

  11. University of Arizona , Tucson, Arizona, USA

    Carlos Scheidegger

  12. Université Paris-Sud , Orsay, France

    Tobias Isenberg

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© 2016 Springer International Publishing AG

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Nguyen, C.D.T., Cho, K.Y., Jang, Y.H., Kim, KS., Kim, S. (2016). Improved Stereo Vision of Indoor Dense Suspended Scatterers Scenes from De-scattering Images. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2016. Lecture Notes in Computer Science(), vol 10072. Springer, Cham. https://doi.org/10.1007/978-3-319-50835-1_47

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  • DOI: https://doi.org/10.1007/978-3-319-50835-1_47

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-50834-4

  • Online ISBN: 978-3-319-50835-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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