Technique for person re-identification using deep ranking

Abstract

The system present a coherent, discriminative framework for simultaneously tracking multiple
people and estimating their collective activities. Instead of treating the two problems separately, our model is
grounded in the intuition that a strong correlation exists between a person's motion, their activity, and the motion
and activities of other nearby people. we introduce a hierarchy of activity types that creates a natural progression
that leads from a specific person's motion to the activity of the group as a whole.