Image collections are a tremendous source of information. Yet due to the
semantic gap it is difficult to get access to their content, while at the
same time it is difficult to properly employ their context such as tags and
metadata. To move forward we propose a multimedia analytics solution. The
most widespread and universally used analytic tools are spreadsheets, where a
powerful feature is the possibility to generate pivot table reports. They
provide flexible interactive summaries of the data along various dimensions.
Pivot tables have been designed and are in use for structured data. Our goal
is creating pivot tables for accessing collections of images, their content,
tags, and metadata. This is a challenging task as automatic descriptors for
image content are noisy, tags are numerous and subjective, and metadata can
have many types. To tackle these challenges we present methods and
visualizations for semi-interactively categorizing an image collection and
from there design and develop pivot tables for such a collection.