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eBook Visual Reconstruction (Artificial Intelligence) epub

by Andrew Zisserman,Andrew Blake

eBook Visual Reconstruction (Artificial Intelligence) epub
  • ISBN: 0262022710
  • Author: Andrew Zisserman,Andrew Blake
  • Genre: Photography
  • Subcategory: Graphic Design
  • Language: English
  • Publisher: The MIT Press (September 21, 1987)
  • Pages: 240 pages
  • ePUB size: 1946 kb
  • FB2 size 1254 kb
  • Formats mobi lit txt rtf


Visual Reconstruction presents a unified and highly original approach to the treatment of continuity in vision.

Visual Reconstruction presents a unified and highly original approach to the treatment of continuity in vision. Series: Artificial Intelligence Series.

Andrew Blake, Andrew Zisserman. Visual Reconstruction presents a unified and highly original approach to the treatment of continuity in vision

Andrew Blake, Andrew Zisserman. Visual Reconstruction presents a unified and highly original approach to the treatment of continuity in vision. It introduces, analyzes, and illustrates two new concepts. The first-the weak continuity constraint-is a concise, computational formalization of piecewise continuity. The book first illustrates the breadth of application of reconstruction processes in vision with results that the authors' theory and program yield for a variety of problems. The mathematics of weak continuity and the graduated nonconvexity (GNC) algorithm are then developed carefully and progressively. Contents: Modeling Piecewise Continuity.

book by Andrew Blake. The first - the weak continuity constraint - is a concise, computational formalization of piecewise continuity.

Visual reconstruction. A Blake, A Zisserman. A Blake, R Curwen, A Zisserman IEEE transactions on pattern analysis and machine intelligence 30 (7), 1270-1281, 2008. P Pérez, M Gangnet, A Blake. ACM Transactions on graphics (TOG) 22 (3), 313-318, 2003. A Blake, R Curwen, A Zisserman. International Journal of Computer Vision 11 (2), 127-145, 1993. IEEE transactions on pattern analysis and machine intelligence 30 (7), 1270-1281, 2008.

Visual Reconstruction - Artificial Intelligence Series (Paperback). Andrew Blake (author), Andrew Zisserman (author). By Andrew Blake and Andrew Zisserman. Out of Print ISBN: 9780262022712 238 pp. 6 in x 9 in September 1987.

Together with Andrew Blake they wrote the book Visual reconstruction published in 1987, which is considered . Visual reconstruction.

Together with Andrew Blake they wrote the book Visual reconstruction published in 1987, which is considered one of the seminal works in the field of computer vision. According to Fitzgibbon (2008) this publication was "one of the first treatments of the energy minimisation approach to include an algorithm (called "graduated non-convexity") designed to directly address the problem of local minima, and furthermore to include a theoretical analysis of its convergence.

Visual Reconstruction book.

Home Computers & Internet Computer Science Artificial Intelligence Computer Vision. Visual Reconstruction by Andrew Blake, Andrew Zisserman. Publisher: The MIT Press 1987 ISBN/ASIN: 0262524066 ISBN-13: 9780262524063 Number of pages: 232. Description: Visual Reconstruction presents a unified and highly original approach to the treatment of continuity in vision.

Visual Reconstruction By Andrew Blake and Andrew Zisserman. Starting from this global stand- point, the book plunges into an in-depth in-

Visual Reconstruction presents a unified and highly original approach to the treatment of continuity in vision. It introduces, analyzes, and illustrates two new concepts. The first - the weak continuity constraint - is a concise, computational formalization of piecewise continuity. It is a mechanism for expressing the expectation that visual quantities such as intensity, surface color, and surface depth vary continuously almost everywhere, but with occasional abrupt changes. The second concept - the graduated nonconvexity algorithm - arises naturally from the first. It is an efficient, deterministic (nonrandom) algorithm for fitting piecewise continuous functions to visual data. The book first illustrates the breadth of application of reconstruction processes in vision with results that the authors' theory and program yield for a variety of problems. The mathematics of weak continuity and the graduated nonconvexity (GNC) algorithm are then developed carefully and progressively. Contents: Modeling Piecewise Continuity. Applications of Piecewise Continuous Reconstruction. Introducing Weak Continuity Constraints. Properties of the Weak String and Membrane. Properties of Weak Rod and Plate. The Discrete Problem. The Graduated Nonconvexity (GNC) Algorithm. Appendixes: Energy Calculations for the String and Membrane. Noise Performance of the Weak Elastic String. Energy Calculations for the Rod and Plate. Establishing Convexity. Analysis of the GNC Algorithm. Both authors are in the Department of Computer Science at the University of Edinburgh. Andrew Blake is Lecturer and a Royal Society IBM Research Fellow. Andrew Zisserman is a Science and Engineering Research Council (SERC) Research Fellow. Visual Reconstruction is included in the Artificial Intelligence series, edited by Michael Brady and Patrick Winston.
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