{"title":"使用可见地标生成路线方向","authors":"Davide Russo, S. Zlatanova, Eliseo Clementini","doi":"10.1145/2676528.2676530","DOIUrl":null,"url":null,"abstract":"The aim of this research is to investigate how to communicate route directions for wayfinding assistance in indoor environments including visible landmarks along the route. We propose an algorithm to automatically generate low level directions, as an XML file, that can be later translated in other languages, e.g., IndoorGML. The most suitable data model is a graph with openings (doors, windows, passages), features and concave corners as nodes, and edges based on geometrical visibility between them. For a given route, the proposed algorithm extracts all the surrounding visible nodes and groups them to simplify subsequent textual instructions. This process is then implemented in a software prototype, \"IndoorNav\", based on an Android device. It uses QRcode scanning for locating user position, calculates the best route to follow, generates low-level route directions, and translates them into textual instructions in the requested language; finally, it shows them to users.","PeriodicalId":164337,"journal":{"name":"International Symposium on Algorithms","volume":"63 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"Route directions generation using visible landmarks\",\"authors\":\"Davide Russo, S. Zlatanova, Eliseo Clementini\",\"doi\":\"10.1145/2676528.2676530\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The aim of this research is to investigate how to communicate route directions for wayfinding assistance in indoor environments including visible landmarks along the route. We propose an algorithm to automatically generate low level directions, as an XML file, that can be later translated in other languages, e.g., IndoorGML. The most suitable data model is a graph with openings (doors, windows, passages), features and concave corners as nodes, and edges based on geometrical visibility between them. For a given route, the proposed algorithm extracts all the surrounding visible nodes and groups them to simplify subsequent textual instructions. This process is then implemented in a software prototype, \\\"IndoorNav\\\", based on an Android device. It uses QRcode scanning for locating user position, calculates the best route to follow, generates low-level route directions, and translates them into textual instructions in the requested language; finally, it shows them to users.\",\"PeriodicalId\":164337,\"journal\":{\"name\":\"International Symposium on Algorithms\",\"volume\":\"63 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-11-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Symposium on Algorithms\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2676528.2676530\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Symposium on Algorithms","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2676528.2676530","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Route directions generation using visible landmarks
The aim of this research is to investigate how to communicate route directions for wayfinding assistance in indoor environments including visible landmarks along the route. We propose an algorithm to automatically generate low level directions, as an XML file, that can be later translated in other languages, e.g., IndoorGML. The most suitable data model is a graph with openings (doors, windows, passages), features and concave corners as nodes, and edges based on geometrical visibility between them. For a given route, the proposed algorithm extracts all the surrounding visible nodes and groups them to simplify subsequent textual instructions. This process is then implemented in a software prototype, "IndoorNav", based on an Android device. It uses QRcode scanning for locating user position, calculates the best route to follow, generates low-level route directions, and translates them into textual instructions in the requested language; finally, it shows them to users.