[PDF.59sw] Local Invariant Features for 3D Image Analysis: Dissertation

Local Invariant Features for 3D Image Analysis: Dissertation

[PDF.xv35] Local Invariant Features for 3D Image Analysis: Dissertation

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 |  2009-09-11 |  2009-09-11 | Original language:English | PDF # 1 |  8.66 x.60 x5.91l,.86 | File type: PDF | 264 pages

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||About the Author|Janis Fehr is a postdoctoral researcher at the HeidelbergCollaboratory for Image Processing (HCI). His research interestsinclude invariant/robust feature design, biomedical imageanalysis and machine learning.

In this thesis, we present a novel framework which provides generic methods for the automatic analysis of 3D volume data. We combine local invariant feature descriptors with learning techniques to infer mathematical models describing 3D objects (structures) in dense and cluttered data. Using annotated training examples, our overall framework is able to adapt to a wide range of different problems by learning local formations of shape and texture properties. Local feature ...

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