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A Fast 3D Indoor-Localization Approach Based on Video Queries

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MultiMedia Modeling (MMM 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9517))

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Abstract

Image-based localization systems are typically used in outdoor environments, as high localization accuracy can be achieved particularly near tall buildings where the GPS signal is weak. Weak GPS signal is also a critical issue for indoor environments. In this paper, we introduce a novel fast 3D Structure-from-Motion (SfM) model based indoor localization approach using videos as queries. Different from an outdoor environment, the captured images in an indoor environment usually contain people, which often leads to an incorrect camera pose estimation. In our approach, we segment out people in the videos by means of an optical flow technique. This way, we filter people in video and complete the captured video for localization. A graph matching based verification is adopted to enhance both the number of images that are registered and the camera pose estimation. Furthermore, we propose an initial correspondence selection method based on local feature ratio test instead of traditional RANSAC which leads to a much faster image registration speed. The extensive experimental results show that our proposed approach has multiple advantages over existing indoor localization systems in terms of accuracy and speed.

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Author information

Authors and Affiliations

  1. Department of Computer and Information Sciences, University of Delaware, Newark, USA

    Guoyu Lu, Abhishek Kolagunda & Chandra Kambhamettu

  2. Department of Information Engineering and Computer Science, University of Trento, Trento, Italy

    Yan Yan

Authors
  1. Guoyu Lu
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  2. Yan Yan
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  3. Abhishek Kolagunda
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  4. Chandra Kambhamettu
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Corresponding author

Correspondence to Guoyu Lu .

Editor information

Editors and Affiliations

  1. University of Texas at San Antonio, San Antonio, USA

    Qi Tian

  2. Dept. of Information Engineering, University of Trento, Povo, Trento, Italy

    Nicu Sebe

  3. EECS, University of Central Florida, Orlando, Florida, USA

    Guo-Jun Qi

  4. EURECOM, Sophia-Antipolis, France

    Benoit Huet

  5. Hefei University of Technology, Hefei, Anhui, China

    Richang Hong

  6. School of Computing and Information, Hefei University of Technology, Hefei, Anhui, China

    Xueliang Liu

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© 2016 Springer International Publishing Switzerland

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Lu, G., Yan, Y., Kolagunda, A., Kambhamettu, C. (2016). A Fast 3D Indoor-Localization Approach Based on Video Queries. In: Tian, Q., Sebe, N., Qi, GJ., Huet, B., Hong, R., Liu, X. (eds) MultiMedia Modeling. MMM 2016. Lecture Notes in Computer Science(), vol 9517. Springer, Cham. https://doi.org/10.1007/978-3-319-27674-8_20

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  • DOI: https://doi.org/10.1007/978-3-319-27674-8_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27673-1

  • Online ISBN: 978-3-319-27674-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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