{"title":"用于视障人士基于图像的室内导航的可穿戴计算","authors":"Gladys Garcia, A. Nahapetian","doi":"10.1145/2811780.2811959","DOIUrl":null,"url":null,"abstract":"In this paper, an image-based non-obtrusive indoor navigation system for the visually impaired is presented. The system makes use of image processing algorithms to extract floor regions from images captured from a wearable eye-mounted heads-up display device. A prototype system called VirtualEyes is presented, where floor regions are analyzed to provide the user with voiced guidance for navigation. The floor detection algorithm was tested against over 200 images captured from indoor corridors of various lighting conditions and achieved up to 81.8% accuracy.","PeriodicalId":102963,"journal":{"name":"Proceedings of the conference on Wireless Health","volume":"107 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":"{\"title\":\"Wearable computing for image-based indoor navigation of the visually impaired\",\"authors\":\"Gladys Garcia, A. Nahapetian\",\"doi\":\"10.1145/2811780.2811959\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, an image-based non-obtrusive indoor navigation system for the visually impaired is presented. The system makes use of image processing algorithms to extract floor regions from images captured from a wearable eye-mounted heads-up display device. A prototype system called VirtualEyes is presented, where floor regions are analyzed to provide the user with voiced guidance for navigation. The floor detection algorithm was tested against over 200 images captured from indoor corridors of various lighting conditions and achieved up to 81.8% accuracy.\",\"PeriodicalId\":102963,\"journal\":{\"name\":\"Proceedings of the conference on Wireless Health\",\"volume\":\"107 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-10-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"18\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the conference on Wireless Health\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2811780.2811959\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the conference on Wireless Health","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2811780.2811959","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Wearable computing for image-based indoor navigation of the visually impaired
In this paper, an image-based non-obtrusive indoor navigation system for the visually impaired is presented. The system makes use of image processing algorithms to extract floor regions from images captured from a wearable eye-mounted heads-up display device. A prototype system called VirtualEyes is presented, where floor regions are analyzed to provide the user with voiced guidance for navigation. The floor detection algorithm was tested against over 200 images captured from indoor corridors of various lighting conditions and achieved up to 81.8% accuracy.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
