January 2018
Intermediate to advanced
268 pages
6h 20m
English
Content preview from OpenCV 3.x with Python By Example - Second Edition
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How does it work?
We start with the seed points specified by the user. This is the bounding box within which we have the object of interest. Underneath the surface, the algorithm estimates the color distribution of the object and the background. The algorithm represents the color distribution of the image as a Gaussian Mixture Markov Random Field (GMMRF). You can refer to the detailed paper to learn more about GMMRF, at http://research.microsoft.com/pubs/67898/eccv04-GMMRF.pdf. We need the color distribution of both the object and the background, because we will be using this knowledge to separate the object. This information is used to find the maximum entropy segmentation by applying the min-cut algorithm to the Markov Random Field. Once ...
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