Variational approaches to image motion segmentation has been an active field of study in
image processing and computer vision for two decades. We present a short overview over …

This article describes the implementation of a simple wavelet-based optical-flow motion
estimator dedicated to continuous motions such as fluid flows. The wavelet representation of …

We present a novel optical flow estimation framework that reinterprets most popular
algorithms (eg, the Horn-Schunck model, PDE-based models, TV-based models, and …

In the context of tackling the ill-posed inverse problem of motion estimation from image
sequences, we propose to introduce prior knowledge on flow regularity given by turbulence …

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 …

Based on a wavelet expansion of the velocity field, we present a novel optical flow algorithm
dedicated to the estimation of continuous motion fields such as fluid flows. This scale-space …

Selecting optimal models and hyperparameters is crucial for accurate optical-flow
estimation. This paper provides a solution to the problem in a generic Bayesian framework …

In this paper, a stochastic formulation of the brightness consistency used in many computer
vision problems involving dynamic scenes (for instance, motion estimation or point tracking) …

Fluid motion estimation from time-sequenced images is a significant image analysis task. Its
application is widespread in experimental fluidics research and many related areas like …

In the context of turbulent fluid motion measurement from image sequences, we propose in
this paper to reverse the traditional point of view of wavelets perceived as an analyzing tool …