Synchronized Data Collection for Human Group Recognition †
Abstract
:1. Introduction
- We identified the synchronized data collection problem in the human group recognition.
- We proposed a trajectory interpolation algorithm to solve different start time and frequency problem in the human group recognition. A reasonable error function is designed to optimize the interpolation.
- We utilize message passing to estimate and minimize the deviation of clocks between devices.
- Extensive evaluations are carried out and the results show that the proposed algorithms outperform the existing approaches.
2. Related Work
3. System Model
4. Aligned Trajectory Interpolation
Algorithm 1: Start time determination |
|
5. Time Deviation Estimation and Elimination
5.1. Time Deviation Estimation Based on Message Passing
5.2. Improvement on the Estimation of Time Deviation
Algorithm 2: Additional Message Passing Determination |
|
6. Evaluation Results
6.1. Evaluation of Aligned Trajectory Interpolation
6.2. Evaluation of Time Deviation Estimation
7. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
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Number of Messages | ||||||||
---|---|---|---|---|---|---|---|---|
(InfNum, AveLength) | 10 | 15 | 20 | 25 | 30 | 35 | 40 | 45 |
Exp.1 | (8, 1.015) | (9, 1.113) | (8, 1.028) | (0, 1.346) | (0, 0.965) | (0, 0.935) | (0, 0.781) | (0, 0.636) |
Exp.2 | (12, inf) | (5, 0.607) | (7, 0.616) | (3, 0.965) | (3, 1.314) | (0, 1.036) | (0, 0.941) | (0, 0.705) |
Exp.3 | (15, inf) | (3, 1.979) | (7, 0.621) | (3, 1.273) | (1, 1.417) | (0, 0.649) | (0, 1.087) | (0, 0.657) |
Exp.4 | (12, inf) | (10, inf) | (2, 0.944) | (0, 1.531) | (0, 1.414) | (1, 0.925) | (0, 0.93) | (0, 0.489) |
Exp.5 | (12, 1.342) | (9, 0.795) | (4, 1.317) | (4, 1.231) | (2, 0.594) | (0, 1.281) | (0, 0.74) | (0, 0.495) |
Average | (11.8, inf) | (7.2, inf) | (5.6, 0.905) | (2.2, 1.269) | (1.4, 1.141) | (0.2, 0.965) | (0, 0.896) | (0, 0.596) |
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Zhu, W.; Xu, L.; Tang, Y.; Xie, R. Synchronized Data Collection for Human Group Recognition. Sensors 2021, 21, 7094. https://doi.org/10.3390/s21217094
Zhu W, Xu L, Tang Y, Xie R. Synchronized Data Collection for Human Group Recognition. Sensors. 2021; 21(21):7094. https://doi.org/10.3390/s21217094
Chicago/Turabian StyleZhu, Weiping, Lin Xu, Yijie Tang, and Rong Xie. 2021. "Synchronized Data Collection for Human Group Recognition" Sensors 21, no. 21: 7094. https://doi.org/10.3390/s21217094