Optical flow estimation is one of the oldest and still most active research domains in
computer vision. In 35 years, many methodological concepts have been introduced and …

This paper introduces a robust 2-D cardiac motion estimation method. The problem is
formulated as an energy minimization with an optical flow-based data fidelity term and two …

In existing literature, the distribution of pixel observations is analyzed with models designed
for the video foreground detection task. However, it is possible that the background and …

Previous approaches to background subtraction in freely moving camera typically focus on
improving the accuracy of motion estimation. In this paper, we propose that the accurate …

Visual object tracking is an essential technique for constructing intelligent livestock
management systems. Behavior patterns estimated from the trajectories of animals provide …

Given the extensive heterogeneity and variability, understanding cellular functions and
regulatory mechanisms through the analysis of multi‐omics datasets becomes extremely …

Based on physical laws describing the multiscale structure of turbulent flows, this paper
proposes a regularizer for fluid motion estimation from an image sequence. Regularization …

This work is concerned with the ill-posed inverse problem of estimating turbulent flows from
the observation of an image sequence. From a Bayesian perspective, a divergence-free …

Atmospheric motion vectors (AMVs) extracted from satellite imagery are the only wind
observations with good global coverage. They are important features for feeding numerical …

In this work, we present an efficient optic flow algorithm for the extraction of vertically
resolved 3D atmospheric motion vector (AMV) fields from incomplete hyperspectral image …