Development of a real-time face tracking system based on the MOSSE correlation filter

Abstract

The functioning acceleration of the face tracking system can be achieved by using simultaneously a highprecision neural network face detector for initial face detection and a tracking system based on modern high-speed correlation filters. A face tracking system using a MOSSE correlation filter (filter with minimum output sum of squared errors) is proposed. The proposed system allows tracking a human face at high speed in real time, as well as in various face positions. The proposed approach was tested using image processing and deep learning tools from the MATLAB application. Keywords convolutional neural network, YOLO v3 object detection algorithm, deep learning, MOSSE filter, face tracking