In this work, we take a different strategy and propose a method that simultaneously extract foreground regions in multiple images without any a priori knowledge on the background. The interest arises in many applications where multiple images are considered and where background information are not available, for instance when a single image only is available per viewpoint. We adopt an EM scheme for that, where background and foreground models are updated in one step, and images are segmented in another step using the new model parameters.

Some important features of the approach are as follows. The method is fully automatic and does not require a priori knowledge of any type nor user interactions. In addition, a single camera at different locations or several cameras can be considered. In the latter, cameras do not need to be color calibrated since geometric and not color consistency is enforced between viewpoints.

W. Lee, W. Woo, E. Boyer, "Silhouette Segmentation in Multiple Views," IEEE Trans. on Pattern Analysis and Machine Intelligence, 2011.

W. Lee, W. Woo, E. Boyer, "Identifying Foreground from Multiple Images," 8th Asian Conference on Computer Vision (ACCV2007), Part II, LNCS 4844, pp. 580-589, 2007.