Bayesian networks are a powerful probabilistic representation, and their use for classification has received considerable attention. However, they tend to perform poorly when lear...
We present a novel algorithm for improving the accuracy of structure from motion on video sequences. Its goal is to efficiently recover scene structure and camera pose by using dyn...
Jonathan Mooser, Suya You, Ulrich Neumann, Raphael...
We address the problem of the segmentation of cerebral white matter structures from diffusion tensor images (DTI). DTI can be estimated from a set of diffusion weighted images and...
We study the multi-frame structure from motion problem when the camera translates on a plane with small baselines and arbitrary rotations. This case shows up in many practical appl...
In this paper we propose a new probabilistic relaxation framework to perform robust multiple motion estimation and segmentation from a sequence of images. Our approach uses displa...