{"title":"Tracko:使用蓝牙低功耗和不清信号进行跨设备交互的Ad-hoc移动3D跟踪","authors":"Haojian Jin, Christian Holz, K. Hornbæk","doi":"10.1145/2807442.2807475","DOIUrl":null,"url":null,"abstract":"While current mobile devices detect the presence of surrounding devices, they lack a truly spatial awareness to bring them into the user's natural 3D space. We present Tracko, a 3D tracking system between two or more commodity devices without added components or device synchronization. Tracko achieves this by fusing three signal types. 1) Tracko infers the presence of and rough distance to other devices from the strength of Bluetooth low energy signals. 2) Tracko exchanges a series of inaudible stereo sounds and derives a set of accurate distances between devices from the difference in their arrival times. A Kalman filter integrates both signal cues to place collocated devices in a shared 3D space, combining the robustness of Bluetooth with the accuracy of audio signals for relative 3D tracking. 3) Tracko incorporates inertial sensors to refine 3D estimates and support quick interactions. Tracko robustly tracks devices in 3D with a mean error of 6.5 cm within 0.5 m and a 15.3 cm error within 1 m, which validates Trackoffs suitability for cross-device interactions.","PeriodicalId":103668,"journal":{"name":"Proceedings of the 28th Annual ACM Symposium on User Interface Software & Technology","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"53","resultStr":"{\"title\":\"Tracko: Ad-hoc Mobile 3D Tracking Using Bluetooth Low Energy and Inaudible Signals for Cross-Device Interaction\",\"authors\":\"Haojian Jin, Christian Holz, K. Hornbæk\",\"doi\":\"10.1145/2807442.2807475\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"While current mobile devices detect the presence of surrounding devices, they lack a truly spatial awareness to bring them into the user's natural 3D space. We present Tracko, a 3D tracking system between two or more commodity devices without added components or device synchronization. Tracko achieves this by fusing three signal types. 1) Tracko infers the presence of and rough distance to other devices from the strength of Bluetooth low energy signals. 2) Tracko exchanges a series of inaudible stereo sounds and derives a set of accurate distances between devices from the difference in their arrival times. A Kalman filter integrates both signal cues to place collocated devices in a shared 3D space, combining the robustness of Bluetooth with the accuracy of audio signals for relative 3D tracking. 3) Tracko incorporates inertial sensors to refine 3D estimates and support quick interactions. Tracko robustly tracks devices in 3D with a mean error of 6.5 cm within 0.5 m and a 15.3 cm error within 1 m, which validates Trackoffs suitability for cross-device interactions.\",\"PeriodicalId\":103668,\"journal\":{\"name\":\"Proceedings of the 28th Annual ACM Symposium on User Interface Software & Technology\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-11-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"53\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 28th Annual ACM Symposium on User Interface Software & Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2807442.2807475\",\"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 28th Annual ACM Symposium on User Interface Software & Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2807442.2807475","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 53
摘要
虽然目前的移动设备可以检测周围设备的存在,但它们缺乏真正的空间意识,无法将它们带入用户的自然3D空间。我们提出Tracko,一个在两个或多个商品设备之间的3D跟踪系统,无需添加组件或设备同步。Tracko通过融合三种信号类型来实现这一点。1) Tracko通过蓝牙低能量信号的强弱,推断出其他设备的存在和距离。Tracko交换一系列听不见的立体声,并从设备到达时间的差异中得出一组设备之间的精确距离。卡尔曼滤波器集成了两个信号线索,将配置的设备放置在共享的3D空间中,将蓝牙的鲁棒性与相对3D跟踪的音频信号的准确性相结合。3) Tracko采用惯性传感器来细化3D估计并支持快速交互。Tracko稳健地跟踪3D设备,0.5 m内的平均误差为6.5 cm, 1 m内的平均误差为15.3 cm,验证了trackoff对跨设备交互的适用性。
Tracko: Ad-hoc Mobile 3D Tracking Using Bluetooth Low Energy and Inaudible Signals for Cross-Device Interaction
While current mobile devices detect the presence of surrounding devices, they lack a truly spatial awareness to bring them into the user's natural 3D space. We present Tracko, a 3D tracking system between two or more commodity devices without added components or device synchronization. Tracko achieves this by fusing three signal types. 1) Tracko infers the presence of and rough distance to other devices from the strength of Bluetooth low energy signals. 2) Tracko exchanges a series of inaudible stereo sounds and derives a set of accurate distances between devices from the difference in their arrival times. A Kalman filter integrates both signal cues to place collocated devices in a shared 3D space, combining the robustness of Bluetooth with the accuracy of audio signals for relative 3D tracking. 3) Tracko incorporates inertial sensors to refine 3D estimates and support quick interactions. Tracko robustly tracks devices in 3D with a mean error of 6.5 cm within 0.5 m and a 15.3 cm error within 1 m, which validates Trackoffs suitability for cross-device interactions.