{"title":"A TensorFlow-based Assistive Technology System for Users with Visual Impairments","authors":"Davide Mulfari","doi":"10.1145/3192714.3196314","DOIUrl":null,"url":null,"abstract":"The paper investigates the potential benefits of bringing together Internet of Things and deep learning techniques toward the development of assistive technologies for users with visual disabilities. We propose a computer vision system designed to classify objects in the user's surroundings and to provide its user with an audio description of the detected things. The solution exploits a wearable vision sensor, which is mounted on the user's glasses and controlled by a single board computer running Google TensorFlow framework. With this software layer, the aid may support users in specific environments, e.g., museums. Finally, experiments show promising results in the context of image classification.","PeriodicalId":330095,"journal":{"name":"Proceedings of the Internet of Accessible Things","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Internet of Accessible Things","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3192714.3196314","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
The paper investigates the potential benefits of bringing together Internet of Things and deep learning techniques toward the development of assistive technologies for users with visual disabilities. We propose a computer vision system designed to classify objects in the user's surroundings and to provide its user with an audio description of the detected things. The solution exploits a wearable vision sensor, which is mounted on the user's glasses and controlled by a single board computer running Google TensorFlow framework. With this software layer, the aid may support users in specific environments, e.g., museums. Finally, experiments show promising results in the context of image classification.
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