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• W1500853963 abstract "Due to its importance, video segmentation has regained interest recently. However, there is no common agreement about the necessary ingredients for best performance. This work contributes a thorough analysis of various within- and between-frame affinities suitable for video segmentation. Our results show that a frame-based superpixel segmentation combined with a few motion and appearance-based affinities are sufficient to obtain good video segmentation performance. A second contribution of the paper is the extension of [1] to include motion-cues, which makes the algorithm globally aware of motion, thus improving its performance for video sequences. Finally, we contribute an extension of an established image segmentation benchmark [1] to videos, allowing coarse-to-fine video segmentations and multiple human annotations. Our results are tested on BMDS [2], and compared to existing methods." @default.
• W1500853963 created "2016-06-24" @default.
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• W1500853963 date "2013-01-01" @default.
• W1500853963 modified "2023-09-29" @default.
• W1500853963 title "Video Segmentation with Superpixels" @default.
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• W1500853963 doi "https://doi.org/10.1007/978-3-642-37331-2_57" @default.
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