About this item
- Title
- Mobility aids detection using Convolution Neural Network (CNN)
- Content partner
- University of Waikato
- Collection
- ResearchCommons@Waikato
- Description
The automated detection of disabled persons in surveillance videos to gain data for lobbying access for disabled persons is a largely unexplored application. We train You Only Look Once (YOLO) CNN on a custom database and achieve an accuracy of 92% for detecting disabled pedestrians in surveillance videos. A person is declared disabled if they are detected in the close proximity of a mobility aid. The detection outcome was further categorised into five classes of mobility aids and precision w...
- Format
- Research Paper
- Research format
- Conference item
- Date created
- 2018
- Creator
- Mukhtar, Amir / Cree, Michael J. / Scott, Jonathan B. / Streeter, Lee
- URL
- https://hdl.handle.net/10289/12430
- Related subjects
- convolutional neural network / mobility aids / computer vision / YOLO
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©2023 The Author(s). This is an open-access article under the CCBY license (http://creativecommons.org/licenses/by/4.0/).
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What can I do with this item?
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Report this itemDigitalNZ brings together more than 30 million items from institutions so that they are easy to find and use. This information is the best information we could find on this item. This item was added on 28 March 2019, and updated 24 March 2025.
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