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- W1981015298 abstract "We study unsupervised and supervised recognition of human actions in video sequences. The videos are represented by probability distributions and then meaningfully compared in a probabilistic framework. We introduce two novel approaches outperforming state-of-the-art algorithms when tested on the KTH and Weizmann public datasets: an unsupervised nonparametric kernel-based method exploiting the Maximum Mean Discrepancy test statistic; and a supervised method based on Support Vector Machine with a characteristic kernel specifically tailored to histogram-based information." @default.
- W1981015298 created "2016-06-24" @default.
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- W1981015298 date "2010-05-16" @default.
- W1981015298 modified "2023-09-25" @default.
- W1981015298 title "Novel Kernel-Based Recognizers of Human Actions" @default.
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- W1981015298 doi "https://doi.org/10.1155/2010/202768" @default.
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