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Geometric Level Set Methods in Imaging, Vision, and Graphics
Geometric Level Set Methods in Imaging, Vision, and Graphics
Date: 11 April 2011, 13:35

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Level set methods are emerging techniques for representing, deforming, and recovering structures in an arbitrary dimension across different fields (such as mathematics, fluid dynamics, graphics, imaging, and vision.). Advances in numerical analysis have led to computationally efficient tools for computing and analyzing interface motion within level set frameworks in a host of application settings.
This authoritative, edited survey provides readers with the state-of-the-art in applying level set techniques in the imaging, vision, and graphics domains, presenting thematically grouped chapters contributed by leading experts from both industry and academia. The work bridges the theoretical foundations of level set methods with the latest significant applications. It will assist readers with both the technical aspects of the field as well as its practical ramifications for areas like medical imaging, computer animation, film restoration, video surveillance, visual inspection, and a range of scientific and engineering disciplines.
The edited volume consists of a preface and 24 chapters organized in 9 thematic areas: Level Set Versus Langrangian Methods, Edge Detection & Boundary Extraction, Scale & Vector Image Reconstruction, Grouping, Knowledge-based Segmentation & Registration, Motion Analysis, Computational Stereo & Implicit Surfaces, Medical Image Analysis and Computer Graphics & Simulations.
Topics and features:
* Covers comprehensively the applications of imaging, vision, & graphics
* Includes a helpful introductory survey chapter on level set methods
* Provides a complete overview of concepts and advanced technologies in the field
* Describes leading-edge research, providing insight into a variety of potential avenues for problem solving
* Supplies numerous implementations, examples, and relevant and useful experimental results
This essential resource carefully integrates the theoretical foundations of level set methods with their actual performance capabilities. Its clarity of organization and approach makes the book accessible for researchers and professionals working in the areas of vision, graphics, image processing, robotics, mathematics, and computational geometry.

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