Efficient planar graph cuts with applications in Computer Vision

We present a fast graph cut algorithm for planar graphs. It is based on the graph theoretical work and leads to an efficient method that we apply on shape matching and image segmentation. In contrast to currently used methods in computer vision, the presented approach provides an upper bound for its...

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Bibliographic Details
Published in2009 IEEE Conference on Computer Vision and Pattern Recognition pp. 351 - 356
Main Authors Schmidt, Frank R, Toppe, Eno, Cremers, Daniel
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2009
Subjects
Application software
Computer vision
Dynamic programming
Image reconstruction
Image segmentation
Runtime
Shape
Stereo image processing
Stereo vision
Upper bound
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Summary:We present a fast graph cut algorithm for planar graphs. It is based on the graph theoretical work and leads to an efficient method that we apply on shape matching and image segmentation. In contrast to currently used methods in computer vision, the presented approach provides an upper bound for its runtime behavior that is almost linear. In particular, we are able to match two different planar shapes of N points in O(N 2 log N) and segment a given image of N pixels in O(N log N). We present two experimental benchmark studies which demonstrate that the presented method is also in practice faster than previously proposed graph cut methods: On planar shape matching and image segmentation we observe a speed-up of an order of magnitude, depending on resolution.
ISBN:1424439922
9781424439928
ISSN:1063-6919
1063-6919
DOI:10.1109/CVPR.2009.5206863