Research on a Face Real-time Tracking Algorithm Based on Particle Filter Multi-Feature Fusion

Sensors

Tianping Li¹  Hui Liu²  Wen Wang³  Tao Wang⁴ 

[1] Technology, Shandong University of Finance and Economics, Jinan 250014, China;;School of Computer Science &School of Physics and Electronics, Shandong Normal University, Jinan 250014, China;Shandong Key Laboratory of Medical Physics and Image Processing, School of Physics and Electronics, Shandong Normal University, Jinan 250014, China;

关键词: video face tracking;    particle filter (PF);    features fusion;    updating model;    template drift;   

DOI  :  10.3390/s19051245

来源: DOAJ

【 摘 要 】

With the revolutionary development of cloud computing and internet of things, the integration and utilization of “big data” resources is a hot topic of the artificial intelligence research. Face recognition technology information has the advantages of being non-replicable, non-stealing, simple and intuitive. Video face tracking in the context of big data has become an important research hotspot in the field of information security. In this paper, a multi-feature fusion adaptive adjustment target tracking window and an adaptive update template particle filter tracking framework algorithm are proposed. Firstly, the skin color and edge features of the face are extracted in the video sequence. The weighted color histogram are extracted which describes the face features. Then we use the integral histogram method to simplify the histogram calculation of the particles. Finally, according to the change of the average distance, the tracking window is adjusted to accurately track the tracking object. At the same time, the algorithm can adaptively update the tracking template which improves the accuracy and accuracy of the tracking. The experimental results show that the proposed method improves the tracking effect and has strong robustness in complex backgrounds such as skin color, illumination changes and face occlusion.

【 授权许可】

Unknown