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• W2567505985 abstract "Many computer vision applications compare the shapes of objects, but few papers provide meaningful comparisons between different shape distance metrics. This paper will begin by summarily describing six metrics that are widely used in the literature. Then a set of criteria to evaluate metrics will be described and a methodology to test the performance of these metrics will be presented. Finally, experimental results, based on the task of tracking articulated human posture from silhouettes, will be used to determine which metric is best suited to the purpose of human tracking. We find that most of the metrics evaluated herein are valid and perform properly to some extent, but that two of them present more desirable behaviors and robustness to noise." @default.
• W2567505985 created "2017-01-06" @default.
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• W2567505985 date "2016-06-01" @default.
• W2567505985 modified "2023-09-25" @default.
• W2567505985 title "Evaluation of Shape Description Metrics Applied to Human Silhouette Tracking" @default.
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• W2567505985 doi "https://doi.org/10.1109/crv.2016.26" @default.
• W2567505985 hasPublicationYear "2016" @default.
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