Dataset of Public Objects in Uncontrolled Environment for Navigation Aiding

Teng-Lai Wong (), Ka-Seng Chou, Kei-Long Wong and Su-Kit Tang
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Teng-Lai Wong: Faculty of Applied Sciences, Macao Polytechnic University, Macao SAR, China
Ka-Seng Chou: Faculty of Applied Sciences, Macao Polytechnic University, Macao SAR, China
Kei-Long Wong: Faculty of Applied Sciences, Macao Polytechnic University, Macao SAR, China
Su-Kit Tang: Faculty of Applied Sciences, Macao Polytechnic University, Macao SAR, China

Data, 2023, vol. 8, issue 2, 1-17

Abstract: Computer vision is a new approach to navigation aiding that assists visually impaired people to travel independently. A deep learning-based solution implemented on a portable device that uses a monocular camera to capture public objects could be a low-cost and handy navigation aid. By recognizing public objects in the street and estimating their distance from the user, visually impaired people are able to avoid obstacles in the outdoor environment and walk safely. In this paper, we created a dataset of public objects in an uncontrolled environment for navigation aiding. The dataset contains three classes of objects which commonly exist on pavements in the city. It was verified that the dataset was of high quality for object detection and distance estimation, and was ultimately utilized as a navigation aid solution.

Keywords: dataset; navigation aid; public object; deep learning; YOLOv4; computer vision (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2023
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