{"title":"You are Here: Mimicking the Human Thinking Process in Reading Floor-Plans","authors":"Hang Chu, Dong Ki Kim, Tsuhan Chen","doi":"10.1109/ICCV.2015.255","DOIUrl":null,"url":null,"abstract":"A human can easily find his or her way in an unfamiliar building, by walking around and reading the floor-plan. We try to mimic and automate this human thinking process. More precisely, we introduce a new and useful task of locating an user in the floor-plan, by using only a camera and a floor-plan without any other prior information. We address the problem with a novel matching-localization algorithm that is inspired by human logic. We demonstrate through experiments that our method outperforms state-of-the-art floor-plan-based localization methods by a large margin, while also being highly efficient for real-time applications.","PeriodicalId":6633,"journal":{"name":"2015 IEEE International Conference on Computer Vision (ICCV)","volume":"40 1","pages":"2210-2218"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE International Conference on Computer Vision (ICCV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCV.2015.255","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 21
Abstract
A human can easily find his or her way in an unfamiliar building, by walking around and reading the floor-plan. We try to mimic and automate this human thinking process. More precisely, we introduce a new and useful task of locating an user in the floor-plan, by using only a camera and a floor-plan without any other prior information. We address the problem with a novel matching-localization algorithm that is inspired by human logic. We demonstrate through experiments that our method outperforms state-of-the-art floor-plan-based localization methods by a large margin, while also being highly efficient for real-time applications.