SVM Classifier for Automatic Surveillance System
Ahmad Kadri Junoh, Muhammad Naufal Mansor, S.A. Abu, Waheed Ahmad, A.Z. Mukhtar, Siti Fazlina Fauzi · Procedia Engineering · 2012
In this paper we describe a home security system based on SVM Classifier. Images were taken in uncontrolled indoor environment using video cameras of various qualities. Database contains 4,005 static images (in visible and infrared spectrum) of 267 subjects. Images from different quality cameras should mimic real–world conditions and enable robust face recognition algorithms testing, emphasizing different law enforcement and surveillance use case scenarios. In addition to database description, this paper also elaborates on possible uses of the database and proposes a testing protocol. A baseline Haar Cascade Method for face recognition algorithm was tested following the proposed protocol based on SVM Classifier. Other researchers can use these test results as a control algorithm performance score when testing their own algorithms on this dataset. Database is available to research community through the procedure described at http://www.lrv.fri.uni–lj.si/facedb.html