抽象的

Real Time Face Tracking By Using Na�ve Bayes Classifier

Krishna Priya Arni , Satish Ammuloju, Jagan Mohan Vithalachari Gollapalli, Dinesh Bhogapurapu Shaik Azeez

In this paper we have taken up the challenge of real time face tracking. Earlier online tracking algorithm is used for this purpose. This algorithm is data dependent. This algorithm samples the frame and separates pixels into two categories. There occurs a drawback in this method as while comparing pixels these might be a chance of wrong pixels getting matched(the pixels of face portion might get matched with pixels of back ground) and there by error in face recognition might occur. In this project we use “naive-bayes” theorem in order to overcome this drawback. The naive-bayes theorem is a theorem of probability which logically evaluates boundary conditions for matching pixels and thus helps in tracking face aptly. By using multi-scale filters and sparse matrix unwanted pixels can be eliminated thus achieving compression. Hence, using multi-scale filters, sparse matrix and naive-bayes theorem we are implementing “Real time face tracking”.