Research on Eye Location and Head State Detection Based on Integrated Learning

Authors

Yingnian Wu, School of Automation Beijing Information Science and Technology University, Beijing 100192, China;
Mengjia He, School of Automation Beijing Information Science and Technology University, Beijing 100192, China;
Xiang Wei, School of Automation Beijing Information Science and Technology University, Beijing 100192, China;

Abstract

Abstract: For real-time detection of eye location problem, a real-time detection system of human eye based on Viola Jones algorithm is designed. Through the MATLAB, the real-time reading and positioning of the detected human eye pictures are controlled by the external or webcam. Through side view, top view, and upward view, it is shown that the human eye real-time positioning system has good detection effect and robustness. In view of the poor classification effect of small data sets on the head state, the random forest algorithm is used to classify the pitching Angle and yaw Angle by HOG-LBP fusion feature and haar-like feature respectively, and then the obtained pitching Angle and deflection Angle are fused. The accuracy of direct classification is improved by 4.5% compared with the point'04 data set.

Recommended Citation

Wu, Yingnian; He, Mengjia; and Wei, Xiang (2019) "Research on Eye Location and Head State Detection Based on Integrated Learning," Journal of System Simulation: Vol. 31: Iss. 11, Article 20.
DOI: 10.16182/j.issn1004731x.joss.19-FZ0358
Available at: https://dc-china-simulation.researchcommons.org/journal/vol31/iss11/20

First Page

2366

Revised Date

2019-07-30

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.19-FZ0358

Last Page

2373

CLC

TP242.6

Recommended Citation

Wu Yingnian, He Mengjia, Xiang Wei. Research on Eye Location and Head State Detection Based on Integrated Learning[J]. Journal of System Simulation, 2019, 31(11): 2366-2373.

DOI

10.16182/j.issn1004731x.joss.19-FZ0358