Journal of System Simulation
Abstract
Abstract: Recently, low cost full Body Motion Tracking attracted tremendous attentions in the fields of Computer Vision and Automation. Single depth camera-and inertial-based motion tracking systems rapidly have become two primary options for small-business and individual consuming markets, due to their relatively inexpensive price and comparable performance. However, both depth camera-and inertial-based motion tracking systems have inherent disadvantages which cannot be eliminated theoretically and experimentally. For example, depth camera tracking mostly failed in the presence of occlusion while inertial sensor tracking usually suffered from drift errors. Therefore, a novel multiple-sensor fusion approach which seamlessly combined the data measured from a RGB-D Camera and several inertial measurement units (IMU) sensors was presented. The method had the characteristic of low cost and was less likely to be influenced by the environment by introducing several new algorithms, e.g., fast occlusion detection, dynamic threshold determination, and weighted value assignment. Experimental studies show that the method shows superior performance in terms of accuracy, reliability, and robustness.
Recommended Citation
Yang, Zhang; Lin, Xu; and Sun, Guangyi
(2020)
"Motion Tracking System by Direct Fusion of RGB-D Camera and Micro-IMU Sensors,"
Journal of System Simulation: Vol. 27:
Iss.
10, Article 52.
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol27/iss10/52
First Page
2582
Revised Date
2015-07-30
DOI Link
https://doi.org/
Last Page
2588
CLC
TP391.9
Recommended Citation
Zhang Yang, Xu Lin, Sun Guangyi. Motion Tracking System by Direct Fusion of RGB-D Camera and Micro-IMU Sensors[J]. Journal of System Simulation, 2015, 27(10): 2582-2588.
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