Taiga Nishiyama, Daichi Yoshikawa, N. Nishio, K. Tsubouchi
{"title":"AirPlanes","authors":"Taiga Nishiyama, Daichi Yoshikawa, N. Nishio, K. Tsubouchi","doi":"10.1145/3386901.3396599","DOIUrl":null,"url":null,"abstract":"There is growing interest in using augmented reality technology for gaming, navigation, and remote communication. Although 3D space models can be made manually or digitalized using specialized and expensive sensing devices like LiDAR (Light Detection and Ranging), which are costly and time-consuming, the recently developed ARCore for Android and ARkit for iOS are convenient and quick means of developing AR applications. Their recognition performance is poor for flat and monotone walls. This drawback is significant because most walls in indoor environments are flat and only a small portion of them are colorful enough to detect feature points.","PeriodicalId":345029,"journal":{"name":"Proceedings of the 18th International Conference on Mobile Systems, Applications, and Services","volume":"73 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 18th International Conference on Mobile Systems, Applications, and Services","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3386901.3396599","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
There is growing interest in using augmented reality technology for gaming, navigation, and remote communication. Although 3D space models can be made manually or digitalized using specialized and expensive sensing devices like LiDAR (Light Detection and Ranging), which are costly and time-consuming, the recently developed ARCore for Android and ARkit for iOS are convenient and quick means of developing AR applications. Their recognition performance is poor for flat and monotone walls. This drawback is significant because most walls in indoor environments are flat and only a small portion of them are colorful enough to detect feature points.