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High Accurate and Efficient Image Retrieval Method Using Semantics for Visual Indoor Positioning

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Communications, Signal Processing, and Systems (CSPS 2019)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 571))

Abstract

Visual indoor positioning has a wide application because of its good positioning performance without additional hardware requirement. However, as the indoor scenes and complexity increase, the offline database will inevitably become large and the online retrieval time will also become long, which make visual indoor positioning unpractical. To solve this problem, we propose a Semantic and Content-Based Image Retrieval (SCBIR) method. By dividing the offline database into semantic databases with different semantic types, the retrieval scope of the image is reduced, and the retrieval time is reduced. First, we use the semantic segmentation method to detect the semantics. Then we divide different semantic scenes in terms of the image order and basic pattern of the semantics in the scene. Finally we use the images belonging to each different semantic scene to build a semantic database, so as to achieve online accurate and fast image retrieval. The experiment results indicate that the proposed method is suitable for large scale retrieval database, and it can reduce the retrieval time in the online stage on the premise of ensuring the accuracy of image retrieval that is critical for visual indoor positioning.

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Acknowledgements

This paper is supported by National Natural Science Foundation of China (61971162, 61771186, 41861134010) and Heilongjiang Province Natural Science Foundation (F2016019).

Author information

Authors and Affiliations

  1. School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin, 150001, People’s Republic of China

    Jin Dai, Lin Ma & XueZhi Tan

  2. Electronic Engineering College, Heilongjiang University, Harbin, 150080, People’s Republic of China

    Danyang Qin

Authors
  1. Jin Dai
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  2. Lin Ma
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  3. Danyang Qin
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  4. XueZhi Tan
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Corresponding author

Correspondence to Lin Ma .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, University of Texas at Arlington, Arlington, TX, USA

    Qilian Liang

  2. College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, China

    Wei Wang

  3. School of Information and Communication Engineering, Dalian University of Technology, Dalian, Liaoning, China

    Xin Liu

  4. School of Information Science and Technology, Dalian Maritime University, Dalian, Liaoning, China

    Zhenyu Na

  5. School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin, China

    Min Jia

  6. College of Physical and Electronic Information, Tianjin Normal University, Tianjin, China

    Baoju Zhang

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Dai, J., Ma, L., Qin, D., Tan, X. (2020). High Accurate and Efficient Image Retrieval Method Using Semantics for Visual Indoor Positioning. In: Liang, Q., Wang, W., Liu, X., Na, Z., Jia, M., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2019. Lecture Notes in Electrical Engineering, vol 571. Springer, Singapore. https://doi.org/10.1007/978-981-13-9409-6_17

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  • DOI: https://doi.org/10.1007/978-981-13-9409-6_17

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-9408-9

  • Online ISBN: 978-981-13-9409-6

  • eBook Packages: EngineeringEngineering (R0)

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