تقرير
Wheelchair Behavior Recognition for Visualizing Sidewalk Accessibility by Deep Neural Networks
| العنوان: | Wheelchair Behavior Recognition for Visualizing Sidewalk Accessibility by Deep Neural Networks |
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| المؤلفون: | Watanabe, Takumi, Takahashi, Hiroki, Sato, Goh, Iwasawa, Yusuke, Matsuo, Yutaka, Yairi, Ikuko Eguchi |
| سنة النشر: | 2021 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Machine Learning |
| الوصف: | This paper introduces our methodology to estimate sidewalk accessibilities from wheelchair behavior via a triaxial accelerometer in a smartphone installed under a wheelchair seat. Our method recognizes sidewalk accessibilities from environmental factors, e.g. gradient, curbs, and gaps, which influence wheelchair bodies and become a burden for people with mobility difficulties. This paper developed and evaluated a prototype system that visualizes sidewalk accessibility information by extracting knowledge from wheelchair acceleration using deep neural networks. Firstly, we created a supervised convolutional neural network model to classify road surface conditions using wheelchair acceleration data. Secondly, we applied a weakly supervised method to extract representations of road surface conditions without manual annotations. Finally, we developed a self-supervised variational autoencoder to assess sidewalk barriers for wheelchair users. The results show that the proposed method estimates sidewalk accessibilities from wheelchair accelerations and extracts knowledge of accessibilities by weakly supervised and self-supervised approaches. Comment: 15 pages, 6 figures, and 1 table; accepted at 2ND International Workshop on Deep Learning for Human Activity Recognition, held in conjunction with IJCAI-PRICAI 2020, January 2021; will be published at Springer Communications in Computer and Information Science (CCIS) proceedings |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2101.03724 |
| رقم الأكسشن: | edsarx.2101.03724 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |