Face Tracking Using Optical Flow : Development of a Real-Time AdaBoost Cascade Face Tracker

In this paper a novel face tracking approach is presented where optical flow information is incorporated into the Viola-Jones face detection algorithm. In the original algorithm from Viola and Jones face detection is static as information from previous frames is not considered. In contrast to the Viola-Jones face detector and also to other known dynamic enhancements, the proposed facetracker preserves information about near-positives. The algorithm builds a likelihood map from the intermediate results of the Viola-Jones algorithm which is extrapolated using optical flow. The objects get extracted from the likelihood map using image segmentation techniques. All steps can be computed very efficiently in real-time. The tracker is verified on the Boston Head Tracking Database showing that the proposed algorithm outperforms the standard Viola-Jones face detector.This paper follows a master thesis which was written within the double degree master program in Embedded and Intelligent Systems of Salzburg University of Applied Sciences, Austria and Halmstad University, Sweden.