Human Detection In Hours Of Darkness Using Gaussian Mixture Model Algorithm
E. Komagal, Varadarajan Seenivasan, S. Krishna Anand, C.P.Anand raj · International Journal of Information Sciences and Techniques · 2014
Video surveillance systems are very important in our everyday life.Video surveillance applications are used in airports, banks, offices and even our homes to remain us secure.Night vision is the ability to see in low light conditions.Surveillance video may not be seen clearly.Especially under the weak illumination conditions.The details of the image are very poor at night.Most of the previous work has focused on daytime Surveillance.This paper proposes a method of Human detection in hours of darkness (night time) using Gaussian Mixture Model (GMM) in real night environment employing an infrared radiation camera.Infrared video is taken as Input to perform Human detection at night.Then the video was processed using Gaussian mixture model algorithm, it was confirmed that by using this method accurate detection of human at night is possible.