As biometrics can now identify people based on individual measures, it appears prudent to translate these techniques for forensic use. As subjects can conceal features associated with identification, prior convictions have used gait and posture to identify suspect. The locations of human vertices are used within instantaneous posture matching. To derive a measure of confidence in this match, we use an automated analysis to determine the variation in the match measure as a function of increasing database size. We can match subjects between videos and assess the confidence in the match measure. We describe how we can derive a match for suspects recorded performing the same criminal act, in surveillance footage, and assess the confidence. As this is the first study of its kind, it raises many points to consider which can aid refinement not just of the matching procedure, but also constraints on the placement of cameras in surveillance.