Issue No. 05 - Oct. (2017 vol. 25)
Yuanqing Zheng , Department of Computing, The Hong Kong Polytechnic University, Hong Kong
Guobin Shen , Microsoft Research Asia, Beijing, China
Liqun Li , Microsoft Research Asia, Beijing, China
Chunshui Zhao , Microsoft Research Asia, Beijing, China
Mo Li , School of Computer Engineering, Nanyang Technological University, Singapore
Feng Zhao , Microsoft Research Asia, Beijing, China
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 shortcuts whenever possible. In this paper, we describe the key techniques to solve several practical 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 four-step offset, and detect deviation events within nine steps. We also characterize the power consumption of Travi-Navi on various mobile phones.
Wireless fidelity, Indoor navigation, Image capture, Mobile handsets, Image quality, Visualization
Y. Zheng, G. Shen, L. Li, C. Zhao, M. Li and F. Zhao, "Travi-Navi: Self-Deployable Indoor Navigation System," in IEEE/ACM Transactions on Networking, vol. 25, no. 5, pp. 2655-2669, 2017.