This paper presents a method that conbines a set of unsupervised algorithms in order to accurately build large taxonomies from any machine-readable dictionary (MRD). Our aim is to...
Abstract In multi-instance learning, the training set comprises labeled bags that are composed of unlabeled instances, and the task is to predict the labels of unseen bags. This pa...
We present a focus-based method to recover the orientation
of a textured planar surface patch from a single image.
The method exploits the relationship between the orientation
o...
This paper presents a spatio-temporal query language useful for video interpretation and event recognition. The language is suited to describe configurations of objects moving on ...
We propose a new approach to estimate gait kinematics from image sequences taken by a monocular uncalibrated camera. This approach involves two generative models for gait represen...