In this paper, we present a novel framework to carry out computations on tensors, i.e. symmetric positive definite matrices. We endow the space of tensors with an affine-invariant...
Pierre Fillard, Vincent Arsigny, Nicholas Ayache, ...
The extraction of consistent skeletons in the presence of boundary noise is still a problem for most skeletonization algorithms. Many suppress skeletons associated with boundary pe...
The aim of this paper is to achieve seamless image stitching without producing visual artifact caused by severe intensity discrepancy and structure misalignment, given that the inp...
We study unsupervised learning of occluding objects in images of visual scenes. The derived learning algorithm is based on a probabilistic generative model which parameterizes obj...
In this paper, we present a Gaussian mixture model based approach to capture the spatial characteristics of any target signal in a sensor network, and further propose a temporally...