Name
Title | ||
|---|---|---|
iTracker: Towards Sustained Self-Tracking in Dynamic Feature Environment with Smartphones |
Abstract | ||
|---|---|---|
Self-tracking at 6 degrees of freedom in real-time is essential in lots of emerging applications such as VR/AR/MR simulation, indoor navigation, and so on. With the development of built-in sensors in smartphones, many self-tracking solutions have appeared. Many researchers try to utilize vision-based approaches combined with an Inertial Measure Unit (IMU) to realize self-tracking with smartphones. After testing these approaches, however, we find that tracking would be lost in four such common scenarios: 1) When the IMU rotates fast or for a long period of time, it will cause serious delays in orientation tracking; 2) The scenes where background features are not distinct enough; 3) When the smartphone moves fast, image features become quite different in successive frames; 4) Unstructured scenes where background features are not static. To address these issues, we propose iTracker, which utilizes Real-time Step-Length Adaption Algorithm to solve the scenario (1) and a Parallel-Multi-State Local Recovery method to deal with scenarios (2)-(4). Extensive experiments show that iTracker realizes robust and accurate self-tracking in these four scenarios with an error of 0.7% throughout the whole trajectory. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/SAHCN.2019.8824883 | 2019 16th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON) |
Keywords | Field | DocType |
iTracker,dynamic feature environment,smartphone,indoor navigation,vision-based approaches,Inertial Measure Unit,IMU,orientation tracking,background features,image features,Real-time Step-Length Adaption Algorithm,sustained self-tracking,parallel-multistate local recovery method | Inertial frame of reference,Computer vision,Feature (computer vision),Computer science,Degrees of freedom (mechanics),Artificial intelligence,Inertial measurement unit,Self tracking,Trajectory,Distributed computing | Conference |
ISSN | ISBN | Citations |
2155-5486 | 978-1-7281-1208-4 | 0 |
PageRank | References | Authors |
0.34 | 19 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Boyuan Sun | 1 | 0 | 0.34 |
| Qiang Ma | 2 | 167 | 14.03 |
| Zhichao Cao | 3 | 0 | 0.34 |
| Yunhao Liu | 4 | 8810 | 486.66 |