A.R. Debilou  , S. Aouragh  , 
    An HMM-Based Model for Moving Object Detection,
    Asian Journal of Information Technology,
    Volume 5,Issue 10,
    2006,
    Pages 1034-1038,
    ISSN 1682-3915,
    ajit.2006.1034.1038,
    (https://makhillpublications.co/view-article.php?doi=ajit.2006.1034.1038)
    Abstract: A new probabilistic background-foreground model based on Hidden Markov Models (HHMs) is presented. The hidden states of the model enable discrimination between Foreground and Background. This method is composed of two phases. First, an ICE (Iterative Conditional Estimation) algorithm is introduced to learn the unknown HMM parameters.  In  the  second  stage,  each pixel  is  classified  with  an MPM (Maximum Posterior Marginal) classification algorithm. The potential and efficiency of the method have been proven through simulations under Matlab.
    Keywords: Detection;hidden markov model;moving object;estimation;classification;stationary camera