The Semantic Robot Vision Challenge is a new research
competition that is designed to push the state of the art in image
understanding and automatic acquisition of knowledge from large
unstructured databases of images (such as those generally found on the
web).

In this competition, teams will be required to demonstrate a robot
that has the ability to:

  1. Autonomously connect to the Internet and build an object
    classification database sufficient to identify a number of objects
    found on a textual list.
  2. Use this classification database to autonomously search an indoor
    environment for the objects in its list.

Integrating a mobile robot with the vision research adds another
interesting layer of complexity that would not ordinarily be available
in a purely computer vision competition. Semantic understanding of
the objects could also be expanded to scene understanding as well.
Thus, scene context can be used to guide the search for objects in
areas which make the most sense for them to be found (e.g. a stapler
is usually found on a desk rather than on the floor or on a wall).

The Semantic Robotic Vision Challenge

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