Yuanqing Zheng, Guobin Shen, Liqun Li, Chunshui Zhao, Mo Li, and Feng Zhao
We present Travi-Navi – a vision-guided navigation system that enables a self-motivated user to easily bootstrap and deploy indoor navigation services, without comprehensive indoor localization systems or even the availability of floor maps. Travi-Navi records high quality images during the course of a guider’s walk on the navigation paths, collects a rich set of sensor readings, and packs them into a navigation trace. The followers track the navigation trace, get prompt visual instructions and image tips, and receive alerts when they deviate from the correct paths. Travi-Navi also finds the most efficient shortcuts whenever possible. We encounter and solve several challenges, including robust tracking, shortcut identification, and high quality image capture while walking. We implement Travi-Navi and conduct extensive experiments. The evaluation results show that Travi-Navi can track and navigate users with timely instructions, typically within a 4-step offset, and detect deviation events within 9 steps.
|Publisher||ACM – Association for Computing Machinery|
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