In this paper we describe a home security system based on Neural Network 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 ease 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 Neural Network 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/fecedb.html. © 2012 Published by Elsevier Ltd.
Junoh, A. K., Mansor, M. N., Abu, S. A., Wan Ahmad, W. Z., Mukiitar, A. Z., & Fauzi, S. F. (2012). Neural network classifier for automatic surveillance system. In Procedia Engineering (Vol. 38, pp. 1801–1805). Elsevier Ltd. https://doi.org/10.1016/j.proeng.2012.06.221