On Stable Dynamic Background Generation Technique Using Gaussian Mixture Models for Robust Object Detection

Mahfuzul Haque, Manzur Murshed, Manoranjan Paul
2008 2008 IEEE Fifth International Conference on Advanced Video and Signal Based Surveillance  
Gaussian mixture models (GMM) is used to represent the dynamic background in a surveillance video to detect the moving objects automatically. All the existing GMM based techniques inherently use the proportion by which a pixel is going to observe the background in any operating environment. In this paper we first show that such a proportion not only varies widely across different scenarios but also forbids using very fast learning rate. We then propose a dynamic background generation technique
more » ... n conjunction with basic background subtraction which detected moving objects with improved stability and superior detection quality on a wide range of operating environments in two sets of benchmark surveillance sequences.
doi:10.1109/avss.2008.12 dblp:conf/avss/HaqueMP08 fatcat:b7xnilptwba7ji5mynyvgkfdq4