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- W2071650006 abstract "We propose an interactive scheme for segmenting meal images for automated dietary assessment. A smartphone user photographs a meal and marks a few touch points on the resulting image. The segmentation algorithm initializes a set of food segments with the touch points, and grows them using local image features. We evaluate the algorithm with a data set consisting of 300 manually segmented meal images. The precision of segmentation is 0.87, compared with 0.70 for fully automatic segmentation. The results show that the precision of segmentation was significantly improved by incorporating minimal user intervention." @default.
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- W2071650006 date "2012-11-02" @default.
- W2071650006 modified "2023-10-16" @default.
- W2071650006 title "Food region segmentation in meal images using touch points" @default.
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- W2071650006 doi "https://doi.org/10.1145/2390776.2390779" @default.
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