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A Pedestrian Avoidance System for Visual Impaired People Based on Object Tracking Algorithm

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Advances in Internet, Data & Web Technologies (EIDWT 2023)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 161))

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Abstract

Avoiding obstacles and pedestrians during the movement is a challenge for the visual impaired people. With the advancement of computer vision, some new technologies can be applied to improve this problem. In this paper, we proposed a new framework to realize such function based on the object tracking algorithm, FairMOT. Our framework detects the pedestrians around users and alarm users to avoid the collision between them. In our system, we use the 360-degree camera as the system input to record the users’ surrounding situations, and use the VR headset as the output device with a feedback application, that is realized using WebVR technologies. In this paper, we also discuss some experiments of the current system and some further improvement methods according to the results of experiments.

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Author information

Authors and Affiliations

  1. Graduate School and Faculty of Information Science and Electrical Engineering, Kyushu University, Fukuoka, Japan

    Rui Shan

  2. Research Institute for Information Technology, Kyushu University, Fukuoka, Japan

    Wei Shi

  3. School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China

    Zhu Teng

  4. Innovation Center for Educational Resources, Kyushu University, Fukuoka, Japan

    Yoshihiro Okada

Authors
  1. Rui Shan
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  2. Wei Shi
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  3. Zhu Teng
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  4. Yoshihiro Okada
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Corresponding author

Correspondence to Rui Shan .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

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© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Shan, R., Shi, W., Teng, Z., Okada, Y. (2023). A Pedestrian Avoidance System for Visual Impaired People Based on Object Tracking Algorithm. In: Barolli, L. (eds) Advances in Internet, Data & Web Technologies. EIDWT 2023. Lecture Notes on Data Engineering and Communications Technologies, vol 161. Springer, Cham. https://doi.org/10.1007/978-3-031-26281-4_40

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