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...
Continuous attractor neural networks (CANNs) are emerging as promising models for describing the encoding of continuous stimuli in neural systems. Due to the translational invaria...
Every time a user uses the Internet, a wealth of personal information is revealed, either voluntarily or involuntarily. This often causes privacy breaches, specially if the informa...
We present a framework for implementing geometric algorithms involving motion. It is written in C++ and modeled after and makes extensive use of CGAL (Computational Geometry Algor...
Leonidas J. Guibas, Menelaos I. Karavelas, Daniel ...
The perception of a virtual environment depends on the user and the task the user is currently performing in that environment. Models of the human visual system can thus be exploi...
Veronica Sundstedt, Alan Chalmers, Kirsten Cater, ...