V. Filipe, Nuno Faria, H. Paredes, H. Fernandes, J. Barroso
{"title":"使用Kinect设备的盲人辅助引导","authors":"V. Filipe, Nuno Faria, H. Paredes, H. Fernandes, J. Barroso","doi":"10.1145/3019943.3019946","DOIUrl":null,"url":null,"abstract":"This paper proposes a real-time system to provide location based guidance and obstacle avoidance of blind persons in indoor environments. The system integrates navigation features based on visual recognition of markers and the detection and classification of possible obstacles in front of the blind person. The system uses the Microsoft Kinect sensor to acquire RGB-D images of the scene. The RGB camera provides input for a real-time tracking algorithm which identifies a trained set of wall-mounted visual markers. The user's pose is estimated combining marker information with GIS data. Depth information is used to classify nearby obstacles. The results of experimental tests with two blind subjects are presented and discussed.","PeriodicalId":334897,"journal":{"name":"Proceedings of the 7th International Conference on Software Development and Technologies for Enhancing Accessibility and Fighting Info-exclusion","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Assisted Guidance for the Blind Using the Kinect Device\",\"authors\":\"V. Filipe, Nuno Faria, H. Paredes, H. Fernandes, J. Barroso\",\"doi\":\"10.1145/3019943.3019946\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a real-time system to provide location based guidance and obstacle avoidance of blind persons in indoor environments. The system integrates navigation features based on visual recognition of markers and the detection and classification of possible obstacles in front of the blind person. The system uses the Microsoft Kinect sensor to acquire RGB-D images of the scene. The RGB camera provides input for a real-time tracking algorithm which identifies a trained set of wall-mounted visual markers. The user's pose is estimated combining marker information with GIS data. Depth information is used to classify nearby obstacles. The results of experimental tests with two blind subjects are presented and discussed.\",\"PeriodicalId\":334897,\"journal\":{\"name\":\"Proceedings of the 7th International Conference on Software Development and Technologies for Enhancing Accessibility and Fighting Info-exclusion\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 7th International Conference on Software Development and Technologies for Enhancing Accessibility and Fighting Info-exclusion\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3019943.3019946\",\"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 7th International Conference on Software Development and Technologies for Enhancing Accessibility and Fighting Info-exclusion","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3019943.3019946","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Assisted Guidance for the Blind Using the Kinect Device
This paper proposes a real-time system to provide location based guidance and obstacle avoidance of blind persons in indoor environments. The system integrates navigation features based on visual recognition of markers and the detection and classification of possible obstacles in front of the blind person. The system uses the Microsoft Kinect sensor to acquire RGB-D images of the scene. The RGB camera provides input for a real-time tracking algorithm which identifies a trained set of wall-mounted visual markers. The user's pose is estimated combining marker information with GIS data. Depth information is used to classify nearby obstacles. The results of experimental tests with two blind subjects are presented and discussed.