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...
In state-of-the-art image retrieval systems, an image is
represented by a bag of visual words obtained by quantizing
high-dimensional local image descriptors, and scalable
schem...
Zhong Wu (Tsinghua University), Qifa Ke (Microsoft...
Given a query image of an object, our objective is to retrieve all instances of that object in a large (1M+) image database. We adopt the bag-of-visual-words architecture which ha...
Ondrej Chum, James Philbin, Josef Sivic, Michael I...
A recognition scheme that scales efficiently to a large number of objects is presented. The efficiency and quality is exhibited in a live demonstration that recognizes CD-covers...
We look at the problem of location recognition in a large image dataset using a vocabulary tree. This entails finding the location of a query image in a large dataset containing 3...