We propose a method to estimate dense motion vector fields from multi-exposure images. Our approach relies on finding a sparse set of correspondences between features in a single-...
We propose a novel approach for a dense texture-based visualization of vector fields on curved surfaces. Our texture advection mechanism relies on a Lagrangian particle tracing th...
This paper describes a method for establishing dense correspondence between two images in a video sequence (motion) or in a stereo pair (disparity) in case of large displacements....
Moustapha Kardouchi, Janusz Konrad, Carlos V&aacut...
— We present here a hardware–friendly version of the Support Vector Machine (SVM), which is useful to implement its feed–forward phase on limited–resources devices such as ...
In recent years the work on vector field visualization has been concentrated on LIC-based methods. In this paper we propose an alternative solution for the visualization of unstea...