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Stereo Vision Based Distance Estimation and Logo Recognition for the Visually Impaired

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Computers Helping People with Special Needs (ICCHP 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10897))

Abstract

Interpreting images to compute properties of the 3D world is a significant matter of computer vision. Therefore computer vision applications can help people requiring assistance. This paper presents a novel stereo-vision-based perception and navigation approach to assist visually impaired people. Frontal view images of stores in a shopping mall are first searched for logo recognition. Distances to the found logos (store signboards) are estimated by stereo matching. Both logo recognition and stereo matching are based on local image features (keypoint descriptors) calculated via Speeded Up Robust Features (SURF) algorithm. Final refined distances are calculated via statistical filtering and averaging of the individual keypoint distances found by matched keypoint pairs. Experimental results on our self generated stereo dataset of 28 storefront images from various distances and viewpoints demonstrate the performance of the proposed approach.

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References

  1. Bay, H., Tuytelaars, T., Van Gool, L.: SURF: speeded up robust features. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3951, pp. 404–417. Springer, Heidelberg (2006). https://doi.org/10.1007/11744023_32

    Chapter  Google Scholar 

  2. Bradski, G., Kaehler, A.: Learning OpenCV: Computer Vision with the OpenCV Library. O’Reilly Media, Inc., Sebastopol (2008)

    Google Scholar 

  3. Caraiman, S., Morar, A., Owczarek, M., Burlacu, A., Rzeszotarski, D., Botezatu, N., Herghelegiu, P., Moldoveanu, F., Strumillo, P., Moldoveanu, A.: Computer vision for the visually impaired: the sound of vision system. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1480–1489 (2017)

    Google Scholar 

  4. Costa, P., Fernandes, H., Martins, P., Barroso, J., Hadjileontiadis, L.J.: Obstacle detection using stereo imaging to assist the navigation of visually impaired people. Procedia Comput. Sci. 14, 83–93 (2012)

    Article  Google Scholar 

  5. Fernandes, H., Costa, P., Filipe, V., Hadjileontiadis, L., Barroso, J.: Stereo vision in blind navigation assistance. In: 2010 World Automation Congress (WAC), pp. 1–6. IEEE (2010)

    Google Scholar 

  6. Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vision 60(2), 91–110 (2004)

    Article  Google Scholar 

  7. Meijer, P.B.: An experimental system for auditory image representations. IEEE Trans. Biomed. Eng. 39(2), 112–121 (1992)

    Article  Google Scholar 

  8. Molton, N., Se, S., Brady, J., Lee, D., Probert, P.: A stereo vision-based aid for the visually impaired. Image Vis. Comput. 16(4), 251–263 (1998)

    Article  Google Scholar 

  9. Schauerte, B., Martinez, M., Constantinescu, A., Stiefelhagen, R.: An assistive vision system for the blind that helps find lost things. In: Miesenberger, K., Karshmer, A., Penaz, P., Zagler, W. (eds.) ICCHP 2012. LNCS, vol. 7383, pp. 566–572. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-31534-3_83

    Chapter  Google Scholar 

  10. Wang, S., Tian, Y.: Camera-based signage detection and recognition for blind persons. In: Miesenberger, K., Karshmer, A., Penaz, P., Zagler, W. (eds.) ICCHP 2012. LNCS, vol. 7383, pp. 17–24. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-31534-3_3

    Chapter  Google Scholar 

  11. Zelek, J.S., Bromley, S., Asmar, D., Thompson, D.: A haptic glove as a tactile-vision sensory substitution for wayfinding. J. Vis. Impair. Blind. 97(10), 621–632 (2003)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Computer Engineering, Istanbul Technical University, Istanbul, Turkey

    Mehmet Biberci & Ulug Bayazit

Authors
  1. Mehmet Biberci
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  2. Ulug Bayazit
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Corresponding author

Correspondence to Mehmet Biberci .

Editor information

Editors and Affiliations

  1. Johannes Kepler University Linz, Linz, Austria

    Klaus Miesenberger

  2. National and Kapodistrian University of Athens, Athens, Greece

    Georgios Kouroupetroglou

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Biberci, M., Bayazit, U. (2018). Stereo Vision Based Distance Estimation and Logo Recognition for the Visually Impaired. In: Miesenberger, K., Kouroupetroglou, G. (eds) Computers Helping People with Special Needs. ICCHP 2018. Lecture Notes in Computer Science(), vol 10897. Springer, Cham. https://doi.org/10.1007/978-3-319-94274-2_11

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  • DOI: https://doi.org/10.1007/978-3-319-94274-2_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-94273-5

  • Online ISBN: 978-3-319-94274-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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