Shape statistics in kernel space for variational image segmentation.

DOI10.1016/S0031-3203(03)00056-6zbMath1035.68125MaRDI QIDQ1400476

Daniel Cremers, Timo Kohlberger, Christoph Schnörr

Publication date: 13 August 2003

Published in: Pattern Recognition (Search for Journal in Brave)

zbMATH Keywords

ImagesegmentationVariational methodsDensity estimationDiffusion snakesNonlinear shape statisticsProbabilistic kernel PCA

Mathematics Subject Classification ID

Computing methodologies for image processing (68U10)

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Cites Work

• Diffusion snakes: Introducing statistical shape knowledge into the Mumford-Shah functional
• Theoretical foundations of the potential function method in pattern recognition learning
• Optimal approximations by piecewise smooth functions and associated variational problems
• Remarks on Some Nonparametric Estimates of a Density Function
• Probabilistic Principal Component Analysis
• Principal Curves
• On Estimation of a Probability Density Function and Mode
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