By mapping a set of input images to points in a lowdimensional manifold or subspace, it is possible to efficiently account for a small number of degrees of freedom. For example, i...
Many vision tasks can be formulated as partitioning an adjacency graph through optimizing a Bayesian posterior probability p defined on the partition-space. In this paper two appr...
We present a new method for summarizing images for the purposes of matching and registration. We take the point of view that large, coherent regions in the image provide a concise...
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 ...
The state of the art in visual object retrieval from large databases is achieved by systems that are inspired by text retrieval. A key component of these approaches is that local ...
James Philbin, Ondrej Chum, Michael Isard, Josef S...