Interactive Co-segmentation of Objects in Image Collections
Springer Science & Business Media, Nov 9, 2011 - Computers - 46 pages
The authors survey a recent technique in computer vision called Interactive Co-segmentation, which is the task of simultaneously extracting common foreground objects from multiple related images. They survey several of the algorithms, present underlying common ideas, and give an overview of applications of object co-segmentation.
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Chapter 1 Introduction
Chapter 2 An Approach to Interactive Cosegmentation
Chapter 3 Applications
Chapter 4 Future of Cosegmentation
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3D model Best appearance model approach average Bagon baseline Batra best image capture Chapter Chen CMU-Cornell iCoseg Dataset co-segment co-segmentation accuracy co-segmentation algorithm collection of images Computer Vision CVPR cyan color Distance Transform distribution energy function energy minimization entropy even-split exhaustively examine foreground and background freeform scribbling girl-pair graph cuts ground-truth group of images histogram matching term ICCV Image Collections image segmentation images given interactive co-segmentation intuition iteration Kolmogorov Kowdle labelled machine experiments mentation model Best viewed multiple images non-planar objects number of images object of interest octree Parikh performance photo collage photo collection planar Potts model reconstruction algorithms Resulting silhouettes Rother sample novel views scale change scene scrib Scribble Length pixels scribbles on multiple seed image selection seed-image segmentation accuracy selection algorithm SIGGRAPH silhouettes after co-segmentation single image Subset super-linear superpixel leaks synthetic scribbles techniques texture map unsupervised co-segmentation user scribbles User Study video cutout viewed in color