Detecting the Moving Object in Dynamic Backgrounds by using Fuzzy-Extreme Learning Machine

摘要

Moving object detection in dynamic background is the important features in video surveillance systems. Detecting the moving object using the SOM in video streams are not suitable for dynamic background and it requires complex computation to adjust the threshold values based on HSV. This paper proposes Fuzzy-Extreme Learning Machine (FELM) for detecting the object in dynamic backgrounds. The proposed model involves Fuzzy-Extreme Learning Machine and Self Organizing Map (SOM) which are used to detect the moving objects as well as shadow elimination in dynamic background. Again it automatically determines the threshold values for various video sequences. The proposed approach identifies the moving objects automatically without human intervention and eliminates the shadows more effectively when compared to other existing methods in the recent literature.