Abstract— Our noncausal, nonparametric, multiscale, Markov random field (MRF) model is capable of synthesising and capturing the characteristics of a wide variety of textures, f...
We present conditional random fields, a framework for building probabilistic models to segment and label sequence data. Conditional random fields offer several advantages over hid...
John D. Lafferty, Andrew McCallum, Fernando C. N. ...
We present a novel approach for analyzing two-dimensional (2D) flow field data based on the idea of invariant moments. Moment invariants have traditionally been used in computer vi...
Michael Schlemmer, Manuel Heringer, Florian Morr...
Accurately representing higher-order singularities of vector fields defined on piecewise linear surfaces is a non-trivial problem. In this work, we introduce a concise yet complet...
Wan-Chiu Li, Bruno Vallet, Nicolas Ray, Bruno L...
In this paper, we present an approach for monitoring the positions of vector field singularities in time-dependent datasets. The concept of singularity index is discussed and exte...
Christoph Garth, Xavier Tricoche, Gerik Scheuerman...