An Efficient Hybrid Approach for Detecting and Tracking Moving Objects for Video Surveillance - Shanmugappriya, S.; Mahesh, K. (IJRDO -Journal of Computer Science Engineering, 2017)
In visual surveillance applications, detection and identification of an object in video framesstream is to be considered as critical task. In recent years, researchers designed many algorithmsnamed Background Subtraction, Optical Flow and Temporal Differencing, etc., to detecting thereal time moving object. Among these, background subtraction algorithm used widely because ithas frame difference, approximate median, Gaussian mixture. The aim of the proposed work is todetect real time moving objects could be done efficacy with the help of mixture of Gaussianalgorithm which requires less in memory and produce good in result. Here, unwanted noise canbe removed by using wiener filter, select YCbCr color space for detecting the foreground objectwhich is fit for light / indoor shadow. Further, test has been made on various video clip and fromthe experimental results, complexity is easily reduce as well as foreground objects are detectedwithout noise by using Gaussian mixture model.