Passive Visible Light Tag System for Localization and Posture Estimation

As the development of the Internet of Things, location service plays a more important role in mobile computing. To provide location service for the already deployed devices and objects, we present LiTag, a visible light-based localization and posture estimation solution with commercial off-the-shelf (COTS) cameras. The core of LiTag is based on the design of a chip-less and battery-less optical tag which can show different color patterns from different observation directions. After capturing a photo containing the tag, LiTag can calculate the tag position and posture by combining the color pattern and the geometric relation in camera imaging. To solve the localization ambiguity, we propose an ambiguity-avoidance method based on a projection relationship. LiTag can work with a single camera without calibration, which significantly reduces the calibration overhead and deployment costs. We implement LiTag and evaluate its performance extensively. Results show that LiTag can provide the tag position with a median error of 1 $\rm{cm}$ in the 2D plane, a median error of 5 cm in the 3D space, and posture estimation with a median error of 0.8$^{\circ }$. We believe that LiTag has high potential to provide a low-cost and easy-to-use solution for ubiquitous localization and posture estimation with widely deployed cameras.