In this paper, the problem of how to better estimate spatially adaptive intensity bounds for image restoration is addressed. When the intensity bounds are estimated from a degrade...
Kaaren May, Tania Stathaki, Anthony G. Constantini...
This paper proposes an original inhomogeneous restoration (deconvolution) model under the Bayesian framework. In this model, regularization is achieved, during the iterative resto...
Recently, nonlinear shape models have been shown to improve the robustness and flexibility of segmentation. In this paper, we propose Shape Regularized Active Contour (ShRAC) that...
Pedestrian detection from images is an important and yet challenging task. The conventional methods usually identify human figures using image features inside the local regions. In...
In this work, we propose an unsupervised Bayesian model for the detection of moving objects from dynamic scenes. This unsupervised solution is a three-step approach that uses a st...