Real Time Human Face Detection and Tracking Using Cascade Detectors and Histogram Based Trackers

Human tracking is an important function for automatic surveillance systems using a vision sensor. Human face is one of the most significant factors to detect person(s) in an image. However, in some cases detection with face alone make false detection especially in single-viewpoints. Therefore, it is difficult to identify a person in an image due to the variety of poses, exactly. This paper describes a method for automatic human tracking based on the nose detection in cropped detected face region using Viola-Jones algorithm and the mean shift tracking method. Additionally, the trackability of this method increases by adjusting the algorithm parameters using different experiments in different condition. The validity of the proposed method is shown through experiment.