Moving Object Detection using Background Subtraction, Shadow Removal and Post Processing
Adesh Hardas, Dattatray Bade, Vibha Wali · 2015
In many vision based application identifying moving objects is important and critical task. For different computer vision application Background subtraction is fast way to detect moving object. Background subtraction separates the foreground from background. However, background subtraction is unable to remove shadow from foreground. Moving cast shadow associated with moving object also gets detected making it challenge for video surveillance. The shadow makes it difficult to detect the exact shape of object and to recognize the object. Now days many methods are available for background subtraction. The core of background subtraction is background modeling. Gaussian Mixture model is good balance between accuracy and complexity. For better result post processing is done to output of Gaussian Mixture model. The experimental results give good performance for the proposed method.