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- W2567251966 abstract "In this work, we propose a multi-view temporal video segmentation approach that employs a Gaussian scoring process for determining the best segmentation positions. By exploiting the semantic action information that the dense trajectories video description offers, this method can detect intra-shot actions as well, unlike shot boundary detection approaches. We compare the temporal segmentation results of the proposed method to both single-view and multi-view methods, and also compare the action recognition results obtained on ground truth video segments to the ones obtained on the proposed multi-view segments, on the IMPART multi-view action data set." @default.
- W2567251966 created "2017-01-06" @default.
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- W2567251966 date "2016-09-01" @default.
- W2567251966 modified "2023-09-24" @default.
- W2567251966 title "Multi-view semantic temporal video segmentation" @default.
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- W2567251966 doi "https://doi.org/10.1109/icip.2016.7533100" @default.
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