Local Variation as a Statistical Hypothesis Test

The goal of image oversegmentation is to divide an image into several pieces, each of which should ideally be part of an object. One of the simplest and yet most effective oversegmentation algorithms is known as local variation (LV) Felzenszwalb and Huttenlocher in Efficient graph-based image segmen...

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Veröffentlicht in:	International journal of computer vision 2016-04, Vol.117 (2), p.131-141
Hauptverfasser:	Baltaxe, Michael, Meer, Peter, Lindenbaum, Michael
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Analysis Artificial Intelligence Computer Imaging Computer Science Computer vision Decisions Graph representations Hypotheses Hypothesis testing Image processing Image Processing and Computer Vision Image processing systems Image segmentation Mathematical analysis Methods Pattern Recognition Pattern Recognition and Graphics Probability theory State of the art Statistics Studies Vision Vision systems Watersheds
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