Hierarchical processing requires activity propagating between higher-and lower-order
cortical areas. However, functional neuroimaging studies have chiefly quantified fluctuations …

The objective of sampling in Euclidean spaces is to deal with the reconstruction of a
(bandlimited) function (or more generally by a function in an appropriate Hilbert space) by …

Nowadays 360 video analysis has become a significant research topic in the field since the
appearance of high-quality and low-cost 360 wearable devices. In this paper, we propose a …

In this work we consider optical flow on evolving Riemannian 2-manifolds which can be
parametrised from the 2-sphere. Our main motivation is to estimate cell motion in time-lapse …

In this work we consider brightness and mass conservation laws for motion estimation on
evolving Riemannian 2-manifolds that allow for a radial parametrization from the 2-sphere …

Effective visualization of large, multidimensional image data is a key instrument for data
exploration in biological and medical applications. We propose a method to visualize motion …

Hierarchies form critical scaffolds for top-down processing but are often multiplex. In the
brain, multiple layers of complex hierarchies intersect, dissociate, and re-converge over the …

In this paper we present a decomposition algorithm for computation of the spatial-temporal
optical flow of a dynamic image sequence. We consider several applications, such as the …

This contribution substantially represents a geodetically relevant collection of particularly
valuable material in the diverse approximation areas involving spherical harmonics, splines …

Motion estimation is an omnipresent goal in image analysis and computer vision. An
important task within is optical flow computation in a sequence of images. It addresses the …