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Intersection Navigation for People with Visual Impairment

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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

Utilizing RGB-Depth images acquired by a wearable system, we propose an integrated assistive navigation for visually impaired people at urban intersection, which provides with crosswalk position (where to cross roads), crossing light signal (when to cross roads) and pedestrian state (whether safe to cross roads). Verified by the experiment results on datasets and in field, the proposed approach detects multiple targets at urban intersections robustly and provides visually impaired people with effective assistance.

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References

  1. KrVision: Intoer: auxiliary glasses for people with visual impairments (in Chinese). http://www.krvision.cn/cpjs/

  2. Cheng, R., Wang, K., Yang, K., Long, N., Hu, W., Chen, H., Bai, J., Liu, D.: Crosswalk navigation for people with visual impairments on a wearable device. J. Electron. Imaging 26, 53025 (2017)

    Google Scholar 

  3. Cheng, R., Wang, K., Yang, K., Long, N., Bai, J., Liu, D.: Real-time pedestrian crossing lights detection algorithm for the visually impaired. Multimed. Tools Appl. 1–21 (2017). https://link.springer.com/article/10.1007%2Fs11042-017-5472-5

  4. Mascetti, S., Ahmetovic, D., Gerino, A., Bernareggi, C.: ZebraRecognizer: pedestrian crossing recognition for people with visual impairment or blindness. Pattern Recogn. 60, 405–419 (2016)

    Article  Google Scholar 

  5. Shangguan, L., Yang, Z., Zhou, Z., Zheng, X., Wu, C., Liu, Y.: CrossNavi: enabling real-time crossroad navigation for the blind with commodity phones. In: Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing, pp. 787–798. ACM Press, New York (2014)

    Google Scholar 

  6. Uddin, M.S., Shioyama, T.: Bipolarity and projective invariant-based zebra-crossing detection for the visually impaired. In: 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2005) – Workshops, pp. 22–22. IEEE (2005)

    Google Scholar 

  7. Poggi, M., Nanni, L., Mattoccia, S.: Crosswalk recognition through point-cloud processing and deep-learning suited to a wearable mobility aid for the visually impaired. In: Murino, V., Puppo, E., Sona, D., Cristani, M., Sansone, C. (eds.) ICIAP 2015. LNCS, vol. 9281, pp. 282–289. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-23222-5_35

    Chapter  Google Scholar 

  8. Ivanchenko, V., Coughlan, J., Shen, H.: Crosswatch: a camera phone system for orienting visually impaired pedestrians at traffic intersections. In: Miesenberger, K., Klaus, J., Zagler, W., Karshmer, A. (eds.) ICCHP 2008. LNCS, vol. 5105, pp. 1122–1128. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-70540-6_168

    Chapter  Google Scholar 

  9. Ivanchenko, V., Coughlan, J., Shen, H.: Real-time walk light detection with a mobile phone. In: Miesenberger, K., Klaus, J., Zagler, W., Karshmer, A. (eds.) ICCHP 2010. LNCS, vol. 6180, pp. 229–234. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-14100-3_34

    Chapter  Google Scholar 

  10. Roters, J., Jiang, X., Rothaus, K.: Recognition of traffic lights in live video streams on mobile devices. IEEE Trans. Circ. Syst. Video Technol. 21, 1497–1511 (2011)

    Article  Google Scholar 

  11. Mascetti, S., Ahmetovic, D., Gerino, A., Bernareggi, C., Busso, M., Rizzi, A.: Robust traffic lights detection on mobile devices for pedestrians with visual impairment. Comput. Vis. Image Underst. 148, 123–135 (2016)

    Article  Google Scholar 

  12. Shioyama, T., Wu, H., Nakamura, N.: Measurement of the length of pedestrian crossings and detection of traffic lights from image data. Meas. Sci. Technol. 13, 311 (2002)

    Article  Google Scholar 

  13. Wei, Y., Kou, X., Lee, M.C.: A new vision and navigation research for a guide-dog robot system in urban system. In: 2014 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, pp. 1290–1295. IEEE (2014)

    Google Scholar 

  14. Wang, S., Pan, H., Zhang, C., Tian, Y.: RGB-D image-based detection of stairs, pedestrian crosswalks and traffic signs. J. Vis. Commun. Image Represent. 25, 263–272 (2014)

    Article  Google Scholar 

  15. Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2005), pp. 886–893. IEEE (2005)

    Google Scholar 

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Correspondence to Kaiwei Wang .

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Cheng, R., Wang, K., Lin, S. (2018). Intersection Navigation for People with Visual Impairment. 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_12

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  • DOI: https://doi.org/10.1007/978-3-319-94274-2_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-94273-5

  • Online ISBN: 978-3-319-94274-2

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