- Paperback: 222 pages
- Publisher: Springer; 1 edition (Jun 14 2004)
- Language: German
- ISBN-10: 3540220291
- ISBN-13: 978-3540220299
- Product Dimensions: 23.4 x 15.6 x 1.2 cm
- Shipping Weight: 340 g
- Amazon Bestsellers Rank: #1,750,624 in Books (See Top 100 in Books)
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Product Details |
Product Description
Product Description
Algebraic projective geometry, with its multilinear relations and its embedding into Grassmann-Cayley algebra, has become the basic representation of multiple view geometry, resulting in deep insights into the algebraic structure of geometric relations, as well as in efficient and versatile algorithms for computer vision and image analysis. This book provides a coherent integration of algebraic projective geometry and spatial reasoning under uncertainty with applications in computer vision. Beyond systematically introducing the theoretical foundations from geometry and statistics and clear rules for performing geometric reasoning under uncertainty, the author provides a collection of detailed algorithms. The book addresses researchers and advanced students interested in algebraic projective geometry for image analysis, in statistical representation of objects and transformations, or in generic tools for testing and estimating within the context of geometric multiple-view analysis.
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This thesis is about uncertain geometric reasoning by integrating projective geometry and statistics. Read the first page
Front Cover | Copyright | Table of Contents | Excerpt | Back Cover
This thesis is about uncertain geometric reasoning by integrating projective geometry and statistics. Read the first page
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