This paper presents a framework for recognising realistic human actions captured from unconstrained environments. The novelties of this work lie in three aspects. First, we propos...
Matteo Bregonzio, Jian Li, Shaogang Gong, Tao Xian...
The ability to generate discrete movement with distinct and stable time courses is important for interaction scenarios both between different robots and with human partners, for ca...
Matthias Tuma, Ioannis Iossifidis, Gregor Schö...
Surface registration is a fundamental step in the reconstruction of three-dimensional objects. While there are several fast and reliable methods to align two surfaces, the tools a...
Andrea Torsello, Emanuele Rodola, Andrea Albarelli
In this paper we propose a new method for the simultaneous segmentation and 3D reconstruction of interest point based articulated motion. We decompose a set of point tracks into r...
We study unsupervised learning of occluding objects in images of visual scenes. The derived learning algorithm is based on a probabilistic generative model which parameterizes obj...