Research Article
Indoor Positioning and Navigation Methods Based on Mobile Phone Camera
@INPROCEEDINGS{10.1007/978-3-030-82562-1_39, author={Min Yu and Jiaohao Yu and Hailei Li and Huixia Li and Hang Guo}, title={Indoor Positioning and Navigation Methods Based on Mobile Phone Camera}, proceedings={Multimedia Technology and Enhanced Learning. Third EAI International Conference, ICMTEL 2021, Virtual Event, April 8--9, 2021, Proceedings, Part I}, proceedings_a={ICMTEL}, year={2021}, month={7}, keywords={Coordinate transformation Homography matrix Indoor positioning and navigation Mobile phone localization}, doi={10.1007/978-3-030-82562-1_39} }- Min Yu
Jiaohao Yu
Hailei Li
Huixia Li
Hang Guo
Year: 2021
Indoor Positioning and Navigation Methods Based on Mobile Phone Camera
ICMTEL
Springer
DOI: 10.1007/978-3-030-82562-1_39
Abstract
The vision technology has been used for the indoor positioning based on a mobile phone camera. In this paper, we studied the 2D positioning method by analyzing the single frame image, obtaining the camera’s interior/exterior orientation parameters through the image calibration procedure, and calculating the coordinates with the homography matrix. Further, the mobile phone camera has been used for the indoor navigation. The image data is processed and converted into the mobile phone’s moving distance and the attitude by the coordinate transformation method (a four-parameter fitting model), and the trajectory of the mobile phone can be calculated by the visual navigation method. In the first experiment, four points have been selected as the calibration points, and the positioning method has been conducted and analyzed. The experimental results with the software GIANT show that the error is 0.192 m in the area 9.6 m × 3.2 m, which reached a high accuracy of the indoor positioning. In the second experiment, a mobile phone has been moved inside the lab room, image data was collected, the trajectory was calculated with the navigation method proposed, and the mean error of 0.685 m has been obtained. Both results explained that the proposed methods can effectively improve the accuracy and stability of indoor positioning and navigation.
