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Gerald Sommer

    Doderer, das Kriminelle und der literarische Kriminalroman
    Vom "Sinn aller Metaphorie"
    Computer analysis of images and patterns
    Algebraic frames for the perception action cycle
    Robot vision
    Geometric computing with Clifford algebra
    • 2008

      Robot vision

      • 468 pages
      • 17 hours of reading

      In 1986, B. K. P. Horn published a book entitled Robot Vision, which actually discussed a wider ? eld of subjects, basically addressing the ? eld of computer vision, but introducing “robot vision” as a technical term. Since then, the - teraction between computer vision and research on mobile systems (often called “robots”, e. g., in an industrial context, but also including vehicles, such as cars, wheelchairs, tower cranes, and so forth) established a diverse area of research, today known as robot vision. Robot vision (or, more general, robotics) is a fast-growing discipline, already taught as a dedicated teaching program at university level. The term “robot vision” addresses any autonomous behavior of a technical system supported by visual sensoric information. While robot vision focusses on the vision process, visual robotics is more directed toward control and automatization. In practice, however, both ? elds strongly interact. Robot Vision 2008 was the second international workshop, counting a 2001 workshop with identical name as the ? rst in this series. Both workshops were organized in close cooperation between researchers from New Zealand and Germany, and took place at The University of Auckland, New Zealand. Participants of the 2008 workshop came from Europe, USA, South America, the Middle East, the Far East, Australia, and of course from New Zealand.

      Robot vision
    • 2001

      Clifford algebra, then called geometric algebra, was introduced more than a cenetury ago by William K. Clifford, building on work by Grassmann and Hamilton. Clifford or geometric algebra shows strong unifying aspects and turned out in the 1960s to be a most adequate formalism for describing different geometry-related algebraic systems as specializations of one „mother algebra“ in various subfields of physics and engineering. Recent work outlines that Clifford algebra provides a universal and powerfull algebraic framework for an elegant and coherent representation of various problems occuring in computer science, signal processing, neural computing, image processing, pattern recognition, computer vision, and robotics. This monograph-like anthology introduces the concepts and framework of Clifford algebra and provides computer scientists, engineers, physicists, and mathematicians with a rich source of examples of how to work with this formalism.

      Geometric computing with Clifford algebra
    • 1997

      The book constitutes the refereed proceedings of the International Workshop on Algebraic Frames for the Perception-Action Cycle, AFPAC '97, held in Kiel, Germany, in September 1997. The volume presents 12 revised full papers carefully reviewed and selected for inclusion in the book. Also included are 10 full invited papers by leading researchers in the area providing a representative state-of-the-art assessment of this rapidly growing field. The papers are organized in topical sections on PAC systems, low level and early vision, recognition of visual structure, processing of 3D visual space, representation and shape perception, inference and action, and visual and motor neurocomputation.

      Algebraic frames for the perception action cycle
    • 1997

      Computer analysis of images and patterns

      • 737 pages
      • 26 hours of reading

      This book constitutes the refereed proceedings of the 7th International Conference on Computer Analysis of Images and Patterns, CAIP '97, held in Kiel, Germany, in September 1997. The volume presents 92 revised papers selected during a double-blind reviewing process from a total of 150 high-quality submissions. The papers are organized in topical sections on pattern analysis, object recognition and tracking, invariants, applications, shape, texture analysis, motion calibration, low-level processing, structure from motion, stereo and correspondence, segmentation and grouping, mathematical morphology, pose estimation, and face analysis.

      Computer analysis of images and patterns