Efficient Algorithms for Global Optimization Methods in Computer Vision - International Dagstuhl Seminar, Dagstuhl Castle, Germany, November 20-25, 2011, Revised Selected Papers (Paperback, 2014 ed.)


This book constitutes the thoroughly refereed post-conference proceedings of the International Dagstuhl-Seminar on Efficient Algorithms for Global Optimization Methods in Computer Vision, held in Dagstuhl Castle, Germany, in November 2011. The 8 revised full papers presented were carefully reviewed and selected by 12 lectures given at the seminar. The seminar focused on the entire algorithmic development pipeline for global optimization problems in computer vision: modelling, mathematical analysis, numerical solvers and parallelization. In particular, the goal of the seminar was to bring together researchers from all four fields to analyze and discuss the connections between the different stages of the algorithmic design pipeline.

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Product Description

This book constitutes the thoroughly refereed post-conference proceedings of the International Dagstuhl-Seminar on Efficient Algorithms for Global Optimization Methods in Computer Vision, held in Dagstuhl Castle, Germany, in November 2011. The 8 revised full papers presented were carefully reviewed and selected by 12 lectures given at the seminar. The seminar focused on the entire algorithmic development pipeline for global optimization problems in computer vision: modelling, mathematical analysis, numerical solvers and parallelization. In particular, the goal of the seminar was to bring together researchers from all four fields to analyze and discuss the connections between the different stages of the algorithmic design pipeline.

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Product Details

General

Imprint

Springer-Verlag

Country of origin

Germany

Series

Image Processing, Computer Vision, Pattern Recognition, and Graphics, 8293

Release date

April 2014

Availability

Expected to ship within 10 - 15 working days

First published

2014

Editors

, ,

Dimensions

235 x 155 x 10mm (L x W x T)

Format

Paperback

Pages

175

Edition

2014 ed.

ISBN-13

978-3-642-54773-7

Barcode

9783642547737

Categories

LSN

3-642-54773-7



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