We present a common variational framework for dense depth recovery and dense three-dimensional motion field estimation from multiple video sequences, which is robust to camera spe...
Jean-Philippe Pons, Renaud Keriven, Olivier D. Fau...
This paper describes a novel application of Statistical Learning Theory (SLT) to control model complexity in flow estimation. SLT provides analytical generalization bounds suitabl...
Zoran Duric, Fayin Li, Harry Wechsler, Vladimir Ch...
In this paper, we address the topic of estimating two-frame dense optical flow from the monogenic curvature tensor. The monogenic curvature tensor is a novel image model, from whi...
Di Zang, Lennart Wietzke, Christian Schmaltz, Gera...
Variational methods are among the most accurate techniques for estimating the optic flow. They yield dense flow fields and can be designed such that they preserve discontinuities, ...
In this paper, we present a method for tracking and retexturing of garments that exploits the entire image information using the optical flow constraint instead of working with di...