Research about Method of Face Detection and Tracking Based on Active Vision

Authors

Enzeng Dong, Complex System Control Theory and Application Key Laboratory, School of Electrical Engineering, Tianjin University of Technology, Tianjin 300384, China;
Shengxu Yan, Complex System Control Theory and Application Key Laboratory, School of Electrical Engineering, Tianjin University of Technology, Tianjin 300384, China;
Jigang Tong, Complex System Control Theory and Application Key Laboratory, School of Electrical Engineering, Tianjin University of Technology, Tianjin 300384, China;

Abstract

Abstract: Based on the method of combining the Camshift algorithm mixing Kalman filter with Adaboost algorithm, a face-detection and tracking algorithm on the active vision was proposed. The algorithm proposed realized the face automatic detection and tracking by using Adaboost algorithm and Camshift mixed algorithm; according to the positional relation of target centroid and the view centre, and the difference of area between the region of the face target and the view, the Pan-Tilt-Zoom (PTZ) control algorithm was designed. Through the rules designed for pan, tilt and zoom control, the algorithm achieved the goal of automatic adjusting the intrinsic parameters of PTZ camera. The active vision algorithm proposed was tested in the hardware platform. The experiment results show that the algorithm has higher efficiency, and can do real-time detecting and tracking human face, which expands the range of camera tracking.

Recommended Citation

Dong, Enzeng; Yan, Shengxu; and Tong, Jigang (2020) "Research about Method of Face Detection and Tracking Based on Active Vision," Journal of System Simulation: Vol. 27: Iss. 5, Article 8.
Available at: https://dc-china-simulation.researchcommons.org/journal/vol27/iss5/8

First Page

973

Revised Date

2014-09-15

DOI Link

https://doi.org/

Last Page

979

CLC

TP391.9

Recommended Citation

Dong Enzeng, Yan Shengxu, Tong Jigang. Research about Method of Face Detection and Tracking Based on Active Vision[J]. Journal of System Simulation, 2015, 27(5): 973-979.