Hierarchical Image Segmentation Using Correlation Clustering

In this paper, we apply efficient implementations of integer linear programming to the problem of image segmentation. The image is first grouped into superpixels and then local information is extracted for each pair of spatially adjacent superpixels. Given local scores on a map of several hundred su...

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Veröffentlicht in:	IEEE transaction on neural networks and learning systems 2016-06, Vol.27 (6), p.1358-1367
Hauptverfasser:	Alush, Amir, Goldberger, Jacob
Format:	Artikel
Sprache:	eng
Schlagworte:	Approximation methods Clustering Clustering algorithms Correlation Correlation clustering Feature extraction hierarchical segmentation Image detection Image segmentation Integer linear programming integer linear programming (ILP) Integer programming Learning Neural networks Probabilistic logic Segmentation
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