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Journal Articles IEEE Transactions on Neural Systems and Rehabilitation Engineering Year : 2021

Dynamic Crosswalk Scene Understanding for the Visually Impaired

Shishun Tian
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Wenbin Zou
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Xia Li
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Lu Zhang

Abstract

Independent mobility poses a great challenge to the visually impaired individuals. This paper proposes a novel system to understand dynamic crosswalk scenes, which detects the key objects, such as crosswalk, vehicle, and pedestrian, and identifies pedestrian traffic light status. The indication of where and when to cross the road is provided to the visually impaired based on the crosswalk scene understanding. Our proposed system is implemented on a head-mounted mobile device (SensingAI G1) equipped with an Intel RealSense camera and a cellphone, and provides surrounding scene information to visually impaired individuals through audio signal. To validate the performance of the proposed system, we propose a crosswalk scene understanding dataset which contains three sub-datasets: a pedestrian traffic light dataset with 7447 images, a dataset of key objects on the crossroad with 1006 images and a crosswalk dataset with 3336 images. Extensive experiments demonstrated that the proposed system was robust and outperformed the state-of-the-art approaches. The experiment conducted with the visually impaired subjects shows that the system is practical useful.
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Dates and versions

hal-03330267 , version 1 (02-06-2023)

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Shishun Tian, Minghuo Zheng, Wenbin Zou, Xia Li, Lu Zhang. Dynamic Crosswalk Scene Understanding for the Visually Impaired. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2021, 29, pp.1478-1486. ⟨10.1109/TNSRE.2021.3096379⟩. ⟨hal-03330267⟩
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