Traditional clustering focuses on finding a single best clustering solution from data. However, given a single data set, one could interpret it in different ways. This is particul...
We present a "parts and structure" model for object category recognition that can be learnt efficiently and in a semisupervised manner: the model is learnt from example ...
We are interested in modeling the variability of different images of the same scene, or class of objects, obtained by changing the imaging conditions, for instance the viewpoint o...
Jeremy D. Jackson, Anthony J. Yezzi, Stefano Soatt...
Automatically discovering common visual patterns from a collection of images is an interesting but yet challenging task, in part because it is computationally prohibiting. Althoug...
We develop nonparametric Bayesian models for multiscale representations of images depicting natural scene categories. Individual features or wavelet coefficients are marginally de...
Jyri J. Kivinen, Erik B. Sudderth, Michael I. Jord...