We survey the emerging area of compression-based, parameter-free, similarity distance measures useful in data-mining, pattern recognition, learning and automatic semantics extracti...
A fast simulatedannealingalgorithmis developed for automatic object recognition. The object recognition problem is addressed as the problem of best describing a match between a hy...
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...
Hybrid generative-discriminative techniques and, in particular, generative score-space classification methods have proven to be valuable approaches in tackling difficult object or...
Alessandro Perina, Marco Cristani, Umberto Castell...
Many visual search and matching systems represent images using sparse sets of "visual words": descriptors that have been quantized by assignment to the best-matching symb...