Current computational models of visual attention focus on bottom-up information and ignore scene context. However, studies in visual cognition show that humans use context to faci...
Aude Oliva, Antonio B. Torralba, Monica S. Castelh...
This paper presents a system that detects humans climbing fences. After extracting a binary blob contour, the system models the human with an extended star-skeleton representation...
The problem of automatic recognition of human activities is among the most important and challenging open areas of research in Computer Vision. This paper presents a new approach ...
Arcangelo Distante, I. Gnoni, Marco Leo, Paolo Spa...
We present an automated algorithm for tissue segmentation of noisy, low contrast magnetic resonance (MR) images of the brain. We use a mixture model composed of a large number of G...
This paper presents a novel discriminative learning technique for label sequences based on a combination of the two most successful learning algorithms, Support Vector Machines an...
Yasemin Altun, Ioannis Tsochantaridis, Thomas Hofm...