Name
Title | ||
|---|---|---|
Design of a Smartphone Indoor Positioning Dynamic Ground Truth Reference System Using Robust Visual Encoded Targets. |
Abstract | ||
|---|---|---|
Smartphone indoor positioning ground truth is difficult to directly, dynamically, and precisely measure in real-time. To solve this problem, this paper proposes and implements a robust smartphone high-precision indoor positioning dynamic real-time ground truth reference system using color visual scatter-encoded targets based on machine vision and photogrammetry. First, a kind of novel high-precision color vision scatter-encoded patterns with a robust recognition rate is designed. Then we use a smartphone to obtain a sequence of images of an experimental room and extract the base points of the color visual scatter-encoded patterns from the sequence images to establish the indoor local coordinate system of the encoded targets. Finally, we use a high-efficiency algorithm to decode the targets of a real-time dynamic shooting image to obtain accurate instantaneous pose information of a smartphone camera and establish the high-precision and high-availability smartphone indoor positioning direct ground truth reference system for preliminary real-time accuracy evaluation of other smartphone positioning technologies. The experimental results show that the encoded targets of the color visual scatter-encoded pattern designed in this paper are easy to detect and identify, and the layout is simple and affordable. It can accurately and quickly solve the dynamic instantaneous pose of a smartphone camera to complete the self-positioning of the smartphone according to the artificial scatter feature visual positioning technology. It is a fast, efficient and low-cost accuracy-evaluation method for smartphone indoor positioning. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.3390/s19051261 | SENSORS |
Keywords | Field | DocType |
smartphone,indoor positioning,visual encoded target,ground truth reference system | Coordinate system,Photogrammetry,Computer vision,Machine vision,Positioning technology,Electronic engineering,Ground truth,Artificial intelligence,Engineering,Color vision | Journal |
Volume | Issue | ISSN |
19 | 5.0 | 1424-8220 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xuan Liao | 1 | 2 | 1.06 |
| Ruizhi Chen | 2 | 402 | 55.33 |
| Ming Li | 3 | 5595 | 829.00 |
| Bingxuan Guo | 4 | 22 | 7.04 |
| Xiaoji Niu | 5 | 281 | 36.22 |
| Weilong Zhang | 6 | 10 | 2.97 |