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A Metric for Tracking Robustness in Real-Time Panorama Acquisition

To test the performance of tracking systems on a high level it is necessary to perform both quantitative and qualitative analyses. This is particularly true for concepts such as robustness that lack a clear-cut quantitative definition. Addressing the difficulty inherent in collecting user evaluation data, we present a metric which maps the quantitative evaluation of systems to a close approximation of qualitative robustness of the experience. This largely reduces the need to perform qualitative analysis of tracking robustness. We motivate the need for this metric through an analysis of four orientation tracking systems used for the construction of environment maps. This initial analysis demonstrates that ground truth error does not directly reflect the results of a qualitative analysis. We then show that our proposed metric is able to use the quantitative analysis of the systems to correctly approximate the relative robustness of the systems in our initial evaluation. Therefore our proposed metric is able to estimate qualitative evaluation results, without the need for an additional user study. Our metric requires only a set of representative video sequences along with ground truth data for each frame in terms of yaw, pitch, and roll.