Abstract:
A surveillance session can he defined as the period between an individual's entrance into a surveillance system.
and their exit. Utilising this framework enables personal features, such as clothing and height estimates, to
become invariant for the duration of the surveillance session. These can then be used as session-based biometrics
tor matching an individual uniquely as they move throughout the surveillance system, which may include
significantly disjoint cameras. By utilising a hierarchy of biometrics to match individuals one can improve the
speed of the overall matching. This eliminate's unlikely matches quickly bv using biometrics that arc fast to
calculate first. This paper proposes height estimation as an example of such a session-based biometric that would
be used earlier in the hierarchy. It demonstrates how statistical height analysis can be quickly calculated as one
of the session-based biometric components used to match the tracks of the same individual through image
sequences taken by two disjoint camera views in the same surveillance session.
