@inproceedings{li2014travi-navi,
author = {Li, Liqun and Zhao, Chunshui and Zhao, Feng and Shen, Jacky},
title = {Travi-Navi: Self-deployable Indoor Navigation System},
booktitle = {Mobicom'14},
year = {2014},
month = {September},
abstract = {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},
url = {http://approjects.co.za/?big=en-us/research/publication/travi-navi-self-deployable-indoor-navigation-system/},
edition = {Mobicom'14},
}