Skip to Main Content
In this paper, we present a novel methodology for tracking performance evaluation. Considering the continuity of the image sequences in a video, we define a new measurement called tracking difficulty which incorporates the local sequence information among a small image sequence centered at each frame. We subsequently use a reflective model to formulate tracking difficulty. Tracking difficulty curves can not only illustrate at which parts of the video one tracking algorithm performs well or poor, but also provide a way to compare the performance of different tracking algorithms. We further add perturbation analysis to the reflective model to examine how sensitive the tracking algorithm is to noise. Results on data sets are presented to show the effectiveness of our evaluation method.