Shape priors in variational image segmentation: Convexity, lipschitz continuity and globally optimal solutions

26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR

Volumn , Issue , 2008, Pages

  Cremers, Daniel ^a   Schmidt, Frank R ^a   Barthel, Frank ^a  

^a UNIVERSITY OF BONN   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER VISION; COPYING; DIGITAL IMAGE STORAGE; EVOLUTIONARY ALGORITHMS; FEATURE EXTRACTION; IMAGE PROCESSING; LEVEL MEASUREMENT; OBJECT RECOGNITION; PATTERN RECOGNITION; PIXELS; PROBABILITY;

CONVEX COMBINATIONS; FUNCTIONALS; IMPLICIT REPRESENTATION; IMPLICIT SHAPE REPRESENTATIONS; LEVEL-SET METHOD; LIPSCHITZ CONTINUITY; LOCAL OPTIMALITY; OPTIMAL SOLUTIONS; PROBABILISTIC REPRESENTATIONS; SEGMENTATION AND TRACKING; SHAPE DEFORMATIONS; SHAPE PRIORS;

IMAGE SEGMENTATION;

EID: 51949103544     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2008.4587446     Document Type: Conference Paper

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