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Updated: Mar 26, 2026

Utilizing vmTracking to Improve the Accuracy of Multi-Animal Pose Estimation in Rodent Social Behavior Studies
07:34

Utilizing vmTracking to Improve the Accuracy of Multi-Animal Pose Estimation in Rodent Social Behavior Studies

Published on: November 7, 2025

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Visual Object Tracking Performance Measures Revisited

Luka Čehovin, Aleš Leonardis, Matej Kristan

    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
    |January 27, 2016
    PubMed

    Abstract:

    The problem of visual tracking evaluation is sporting a large variety of performance measures, and largely suffers from lack of consensus about which measures should be used in experiments. This makes the cross-paper tracker comparison difficult. Furthermore, as some measures may be less effective than others, the tracking results may be skewed or biased toward particular tracking aspects. In this paper, we revisit the popular performance measures and tracker performance visualizations and analyze them theoretically and experimentally. We show that several measures are equivalent from the point of information they provide for tracker comparison and, crucially, that some are more brittle than the others. Based on our analysis, we narrow down the set of potential measures to only two complementary ones, describing accuracy and robustness, thus pushing toward homogenization of the tracker evaluation methodology. These two measures can be intuitively interpreted and visualized and have been employed by the recent visual object tracking challenges as the foundation for the evaluation methodology.

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