Face detection and Tracking are important research areas in the field of computer vision and image processing. Face detection is a computer technology that helps to determine the locations and size of the human faces. Face detection techniques are used in cameras for auto focus. Face detection and tracking are the two processes done by using various approaches. It is applied mainly in surveillance. The main purpose of these processes are detect and track the face even in poor viewing conditions in surveillance application. In this paper various techniques used for people detection and tracking like adaptive color based particle filter, fuzzy based particle filter algorithm and so on are discussed. Comparisons between the various approaches are illustrated, Performance measures in terms of number of particles used, root mean square error values etc have been reported. Drawbacks for the techniques like tracker facing the problems while detection and tracking has been explained. Reasons why fuzzy based particle filter is best among all the approaches have been produced.