Detection of multiple moving objects using multiscale MRF with camera motion compensation

We address the problem of detecting moving objects from a moving camera. The apparent flow field induced by the camera motion is modeled by a 2D parametric motion model and compensated for using the values of the parameters estimated by a multiresolution robust method. Motion detection is achieved through a statistical regularization approach based on multiscale Markov random field (MRF) models. Particular attention has been paid to the definition of the energy function involved and to the considered observations. This method has been validated by experiments carried out on different real image sequences