Large Scale Visual Semantic Extraction
Venue
Frontiers of Engineering - Reports on Leading-Edge Engineering from the 2011 Symposium, The National Academies Press, Washington, D.C. (2012), pp. 61-68
Publication Year
2012
Authors
BibTeX
Abstract
Image annotation is the task of providing textual semantic to new images, by
ranking a large set of possible annotations according to how they correspond to a
given image. In the large scale setting, there could be millions of images to
process and hundreds of thousands of potential distinct annotations. In order to
achieve such a task we propose to build a so-called "embedding space", into which
both images and annotations can be automatically projected. In such a space, one
can then find the nearest annotations to a given image, or annotations similar to a
given annotation. One can even build a visio-semantic tree from these annotations,
that corresponds to how concepts (annotations) are similar to each other with
respect to their visual characteristics. Such a tree will be different from
semantic-only trees, such as WordNet, which do not take into account the visual
appearance of concepts.
