We investigate how to effectively incorporate spatial structure information into histogram features for boosting visual classification performance motivated by recently proposed M...
We present an approach for the supervised online learning of object representations based on a biologically motivated architecture of visual processing. We use the output of a rece...
Nowadays, with the exponential growing of 3D object representations in private databases or on the web, it is all the more required to match these objects from some views. To impr...
Due to the large variation and richness of visual inputs, statistical learning gets more and more concerned in the practice of visual processing such as visual tracking and recogn...
We present a new approximation algorithm based on an exact representation of the state space S, using decision diagrams, and of the transition rate matrix R, using Kronecker algeb...
Andrew S. Miner, Gianfranco Ciardo, Susanna Donate...