We develop an optical flow estimation framework that focuses on motion estimation over time formulated in a Dynamic Bayesian Network. It realizes a spatiotemporal integration of ...
Volker Willert, Marc Toussaint, Julian Eggert, Edg...
Learning temporal graph structures from time series data reveals important dependency relationships between current observations and histories. Most previous work focuses on learn...
We present a gestural interface for entering text on a mobile device via continuous movements, with control based on feedback from a probabilistic language model. Text is represent...
Dynamic sentiment ambiguous adjectives (DSAAs) like "large, small, high, low"pose a challenging task on sentiment analysis. This paper proposes a knowledge-based method ...
Fluid flow in porous media is a dynamic process that is traditionally modeled using PDE (Partial Differential Equations). In this approach, physical properties related to fluid fl...