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Indoor Positioning Solely Based on User’s Sight

  • Conference paper
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Information Science and Applications 2017 (ICISA 2017)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 424))

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Abstract

Determination of the absolute geographical position has become every day routine, using the Global Positioning System (GPS), despite the prior existence of maps. However no equally universal solution has been developed for determining one’s location inside a building, which is an equally relevant problem statement, for which GPS cannot be used. Existing solutions usually involve additional infrastructure on the end of the location provider, such as beacon installations or particular configurations of wireless access points. These solutions are generally facilitated by additional native mobile applications on the client device, which connect to this infrastructure. We are aware of such solutions, but believe these to be lacking in simplicity. Our approach for indoor positioning alleviates the necessity for additional hardware by the provider, and software installation by the user. We propose to determine the user’s position inside a building using only a photo of the corridor visible to the user, uploading it to a local positioning server, accessible using a browser, which performs a classification of the photo based on a Neural Network approach. Our results prove the feasibility of our approach. One floor of the university’s building with partially very similar corridors has been learned by a deep convolutional neural network. A person lost in the building simply accesses the positioning server’s website and uploads a photo of his current line of sight. The server responds by generating and displaying a map of the building with the user’s current position and current direction.

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Notes

  1. 1.

    AT&T Cambridge (http://www.cl.cam.ac.uk/research/dtg/attarchive/).

  2. 2.

    (http://www.gatech.edu/).

  3. 3.

    (http://research.microsoft.com/en-us/).

  4. 4.

    Massachusetts Institute of Technology (http://web.mit.edu/).

  5. 5.

    (http://www.eecs.berkeley.edu/).

  6. 6.

    Scale-invariant-feature-Transform. US 6711293B1, Method and apparatus for identifying scale invariant features in an image and use of same for locating an object in an image.

  7. 7.

    Norm ISO/IEC 10918-1, describing methods for picture compression. The Joint Photographic Experts Group developed the algorithm, thus the name JPEG.

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Correspondence to Matthias Becker .

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Becker, M. (2017). Indoor Positioning Solely Based on User’s Sight. In: Kim, K., Joukov, N. (eds) Information Science and Applications 2017. ICISA 2017. Lecture Notes in Electrical Engineering, vol 424. Springer, Singapore. https://doi.org/10.1007/978-981-10-4154-9_10

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  • DOI: https://doi.org/10.1007/978-981-10-4154-9_10

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-4153-2

  • Online ISBN: 978-981-10-4154-9

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