Assessing tracking assessment measures

We propose a methodology to quantitatively compare the relative performance of tracking evaluation measures. The proposed methodology is based on determining the probabilistic agreement between tracking result decisions made by measures and those made by humans. We use tracking results on publicly available datasets with different target types and varying challenges, and collect the judgments of 90 skilled, semi-skilled and unskilled human subjects using a web-based performance assessment test. The analysis of the agreements allows us to highlight the variation in performance of the different measures and the most appropriate ones for the various stages of tracking performance evaluation.