Tracking Consistency Metric for Video Surveillance Tracking

The aim of this paper is to propose an additional performance tracking metric. The performance of a tracking algorithm depends on the parameters that are being tracked ranging from reference points that cover edges and corners, to blob parameters such as size, trajectory and color. Based on different features used in tracking, the tracking metrics range from contingency tables, rates of correct tracks to error differences between tracked features and reference points. Among the tracking metrics that have been developed were tracker detection rate (TDR), object tracking error (OTE) and contingency table. These metrics give a measure of the ability of a tracking algorithm to correctly detect or track a target object. There has been no metric published or utilized to determine the performance of a tracking algorithm in the consistency of maintaining a correct track on the selected target. This paper proposes a method and metric to give a measure of determining the consistency of a tracking. The results of the proposed TC metric have results that range from 0.81 to 0.35 for TDR of 90%, 0.65 to 0.21 for TDR of 80%, 0.5 to 0.16 for TDR of 70%, 0.37 to 0.12 for TDR of 60% and 0.26 to 0.08 for TDR of 50%.