Template matching approach for automatic human body tracking in video

Abstract

In this paper a novel template matching approach is presented to achieve automatic human body tracking in video sequences. The developed method which is based on a special template matching algorithm applied on a set of interest points detected on the human body contour. The matching approach is based on different types of similarity measures applied on consecutive frames from videos. Each frame was attacked with different types of noise: luminosity variation and motion blur. This new approach considers different matching constraints such as: cross-matching, uniqueness constraint and interest point's appearances and disappearances between consecutive frames. The algorithm was validated on two different datasets and the obtained results are so encouraging with high values of matching rate and good tracking rate.