This paper presents an e cient scheme for a neinvariant object recognition. A ne invariance is obtained by a representation which is based on a new sampling con guration in the fr...
Image understanding requires not only individually estimating elements of the visual world but also capturing the interplay among them. In this paper, we provide a framework for p...
The main achievement of this work is the development of a new face recognition approach called Partial Principal Component Analysis (P2 CA), which exploits the novel concept of us...
Antonio Rama, Francesc Tarres, Davide Onofrio, Ste...
In this paper, we propose a new approach for face shape recovery from a single image. A single near infrared (NIR) image is used as the input, and a mapping from the NIR tensor sp...
We propose the use of latent space models applied to local invariant features for object classification. We investigate whether using latent space models enables to learn patterns...
Florent Monay, Pedro Quelhas, Daniel Gatica-Perez,...