We propose a novel probabilistic framework for learning
visual models of 3D object categories by combining appearance
information and geometric constraints. Objects are
represen...
We propose a novel and robust model to represent and learn generic 3D object categories. We aim to solve the problem of true 3D object categorization for handling arbitrary rotati...
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...
In this paper, we propose a new general additive watermarking model based on the content of digital images, called as CBWM (Content-Based Watermarking Model). It provides a common...
In this paper we propose a new approach for false positive reduction in the field of mammographic mass detection. The goal is to distinguish between the true recognized masses and ...