Image categorization is undoubtedly one of the most challenging open problems faced in Computer Vision, far from being solved by employing pure visual cues. Recently, additional t...
Marco Cristani, Alessandro Perina, Umberto Castell...
Gaussian blurring mean-shift (GBMS) is a nonparametric clustering algorithm, having a single bandwidth parameter that controls the number of clusters. The algorithm iteratively sh...
Graphical models such as Bayesian Networks (BNs) are being increasingly applied to various computer vision problems. One bottleneck in using BN is that learning the BN model param...
Reliable 3D tracking is still a difficult task. Most parametrized 3D deformable models rely on the accurate extraction of image features for updating their parameters, and are pro...
Christian Vogler, Zhiguo Li, Atul Kanaujia, Siome ...
Dominant sets are a new graph-theoretic concept that has proven to be relevant in partitional (flat) clustering as well as image segmentation problems. However, in many computer v...