  Action recognition, motion classification, gait analysis and synthesis are
fundamental problems in a number of fields such as computer graphics,
bio-mechanics and human computer interaction that generate a large body of
research. This type of data is complex because it is inherently
multidimensional and has multiple modalities such as video, motion capture
data, accelerometer data, etc. While some of this data, such as monocular video
are easy to acquire, others are much more difficult and expensive such as
motion capture data or multi-view video. This creates a large barrier of entry
in the research community for data driven research. We have embarked on
creating a new large repository of motion and action data (CAMREP) consisting
of several motion and action databases. What makes this database unique is that
we use a variety of modalities, enabling multi-modal analysis. Presently, the
size of datasets varies with some having a large number of subjects while
others having smaller numbers. We have also acquired long capture sequences in
a number of cases, making some datasets rather large.
