Abstract
A new approach to human tracking was developed through the use of a popular statistical model, known as Principal Component Analysis, for constructing the human eigen-shape model in conjunction with the mean shift tracking algorithm. The regular mean shift tracker focuses on tracking through the use of the rectangle shape. The new approach focuses on using a more precise estimation of a human shape to track the human throughout a video sequence. The entire paper focuses on the localization of human; identification of the human; tracking the identified human by the modified mean shift algorithm. Last but not least, is the updating of the human principal component coefficients in the modified mean shift tracker, so as to update the human shape as it changes.