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16.08.2021 | Long Paper

A dataset for the recognition of obstacles on blind sidewalk

verfasst von: Wu Tang, De-er Liu, Xiaoli Zhao, Zenghui Chen, Chen Zhao

Erschienen in: Universal Access in the Information Society | Ausgabe 1/2023

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Abstract

Recently, the technology of assisting the navigation of visually impaired persons with computer vision has been greatly developed. A number of scholars have conducted related research, including indoor and outdoor object detection for blind people. However, there are still problems with some existing methods or datasets. Our work mainly proposes a dataset (OD) for assisting the detection and recognition of outdoor obstacles for blind people on blind sidewalk. We classify some common obstacles, train the dataset with state-of-the-art detectors to obtain detection models, and then analyze and compare these models in detail. The results show that our proposed dataset is very challenging. The OD and the detection model can be obtained at the following URL: https://github.com/TW0521/Obstacle-Dataset.git.

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Titel: A dataset for the recognition of obstacles on blind sidewalk
verfasst von: Wu Tang
De-er Liu
Xiaoli Zhao
Zenghui Chen
Chen Zhao
Publikationsdatum: 16.08.2021
Verlag: Springer Berlin Heidelberg
Erschienen in: Universal Access in the Information Society / Ausgabe 1/2023
Print ISSN: 1615-5289
Elektronische ISSN: 1615-5297
DOI: https://doi.org/10.1007/s10209-021-00837-9

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