Gesture Recognition Method Based on Multi-feature Fusion

Authors

Yuanming Wang, 1.China State Shipbuilding Corporation System Engineering Research Institute, Beijing 100094, China;;
Zhang Jun, 1.China State Shipbuilding Corporation System Engineering Research Institute, Beijing 100094, China;;
Yuanhui Qin, 1.China State Shipbuilding Corporation System Engineering Research Institute, Beijing 100094, China;;
Xiujuan Chai, 2. Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, The Chinese Academy of Sciences, Beijing 100190, China;

Abstract

Abstract: Aiming at the specific application requirements of command gesture for flight deck, a gesture recognition method based on multi-feature fusion is proposed. The 3D trajectory feature vector and hand sparse representation are established from two aspects of the trajectory and posture based on the visual information collected by depth camera. On the one hand, the gesture is recognized through normalization resampling and alignment based on the trajectory feature. On the other hand, the gesture is recognized through sparse representation alignment based on the HOG feature. The recognition results are fused effectively. The experimental results indicate that our methods greatly enhance accuracy, and have better robustness.

Recommended Citation

Wang, Yuanming; Jun, Zhang; Qin, Yuanhui; and Chai, Xiujuan (2019) "Gesture Recognition Method Based on Multi-feature Fusion," Journal of System Simulation: Vol. 31: Iss. 2, Article 22.
DOI: 10.16182/j.issn1004731x.joss.17-0089
Available at: https://dc-china-simulation.researchcommons.org/journal/vol31/iss2/22

First Page

346

Revised Date

2017-05-09

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.17-0089

Last Page

352

CLC

TP391

Recommended Citation

Wang Yuanming, Zhang Jun, Qin Yuanhui, Chai Xiujuan. Gesture Recognition Method Based on Multi-feature Fusion[J]. Journal of System Simulation, 2019, 31(2): 346-352.

DOI

10.16182/j.issn1004731x.joss.17-0089