We use unsupervised probabilistic machine learning ideas to try to explain the kinds of learning observed in real neurons, the goal being to connect abstract principles of self-or...
This paper presents a monocular vision framework enabling feature-oriented appearance-based navigation in large outdoor environments containing other moving objects. The framework ...
Sinisa Segvic, Anthony Remazeilles, Albert Diosi, ...
We present a template-based approach to detecting human silhouettes in a specific walking pose. Our templates consist of short sequences of 2D silhouettes obtained from motion cap...
Real-world action recognition applications require the development of systems which are fast, can handle a large variety of actions without a priori knowledge of the type of actio...
We propose a method for vision-based scene understanding in urban traffic environments that predicts the appropriate behavior of a human driver in a given visual scene. The method...
Martin Heracles, Fernando Martinelli, Jannik Frits...