Robust realtime face recognition and tracking system

• Main Authors: Kai Chen, Le Jun Zhao
• Format: Article
• Language: English
• Published: Postgraduate Office, School of Computer Science, Universidad Nacional de La Plata 2009-10-01
• Series: Journal of Computer Science and Technology
• Subjects: meanshift; svm; wavelet; realtime face detection; realtime face tracking; face recognition; kalman filter
• Online Access: https://journal.info.unlp.edu.ar/JCST/article/view/721

There s some very important meaning in the study of realtime face recognition and tracking system for the video monitoring and artifical vision. The current method is still very susceptible to the illumination condition, non-real time and very common to fail to track the target face especially when partly covered or moving fast. In this paper, we propose to use Boosted Cascade combined with skin model for face detection and then in order to recognize the candidate faces, they will be analyzed by the hybrid Wavelet, PCA (principle component analysis) and SVM (support vector machine) method. After that, Meanshift and Kalman filter will be invoked to track the face. The experimental results show that the algorithm has quite good performance in terms of real-time and accuracy.