TY  - JOUR
T1  - An HMM-Based Model for Moving Object Detection
AU - , A.R. Debilou AU - , S. Aouragh 
JO  - Asian Journal of Information Technology
VL  - 5
IS  - 10
SP  - 1034
EP  - 1038
PY  - 2006
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2006.1034.1038
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2006.1034.1038
KW  - Detection
KW  -hidden markov model
KW  -moving object
KW  -estimation
KW  -classification
KW  -stationary camera
AB  - 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.
ER  -