Kernel methods are effective approaches to the modeling of structured objects in learning algorithms. Their major drawback is the typically high computational complexity of kernel ...
Fabio Aiolli, Giovanni Da San Martino, Alessandro ...
Given a complete unoriented point set, we propose a binary orientation tree (BOT) for volume and surface representation, which roughly splits the space into the interior and exter...
In Image Compression, the researchers' aim is to reduce the number of bits required to represent an image by removing the spatial and spectral redundancies. Recently discrete...
— Database of human motion has been widely used for recognizing human motion and synthesizing humanoid motions. In this paper, we propose a data structure for storing and extract...
This paper introduces a new formulation for discrete image labeling tasks, the Decision Tree Field (DTF), that combines and generalizes random forests and conditional random fiel...
Sebastian Nowozin, Carsten Rother, Shai Bagon, Ban...