Yet Another Computer Vision Index To Datasets (YACVID) - Details

Stand: 2017-07-23 000000m 22:52:18 - Overview

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Name (Institute + Shorttitle)Grabcut 
Description (include details on usage, files and paper references)To evaluate our method we designed a new ground truth database of 50 images. The following zip-files contain: Data, Segmentation, Labelling - Lasso, Labelling - Rectangle. Due to license issues, please download the following images (readme.txt) from the zip-file available at Berkley Image database. Explanation of the datasets:

Segmentation: A tri-map which specifies background (0), foreground (255) and mixed area (128). The mixed area contains pixels which are a combination of fore- and background texture. Note, in low contrast regions the true boundary is not observed and the ground truth is in this case a "good guess".
Labelling-Lasso: Imitates a tri-map obtained by a lasso or pen tool. The colour coding is: background (0); background - used for colour model training (64); inference (unknown) region (128); foreground - used for colour model training (255). Note, a lasso tool can be imitated by specifying the foreground region (255) as unknown (128).
Labelling-Rectangle: Imitates a tri-map obtained by two mouse clicks (rectangle). Same colour coding as in Labelling-Lasso.
 
URL Linkhttp://research.microsoft.com/en-us/um/cambridge/projects/visionimagevideoediting/segmentation/grabcut.htm 
Files (#)50 
References (SKIPPED)
Category (SKIPPED)Image Segmentation 
Tags (single words, spaced)segmentation, boundingbox, color, optimization, background 
Last Changed2017-07-23 
Turing (2.12+3.25=?) :-)