BMVC91

1. Front Matter

   Pages i-xv

   PDF

2. Image Motion Analysis Made Simple and Fast, One Component at a Time

   • Peter J. Burt

   Pages 1-8

3. Visual Modeling

   • Demetri Terzopoulos

   Pages 9-12

4. Distributed Dynamic Processing for Edge Detection

   • H. Tunley

   Pages 13-21

5. Boundary Detection Using Bayesian Nets

   • N. Bryson, C. J. Taylor

   Pages 22-28

6. Parallel Implementation of Lagrangian Dynamics for real-time snakes

   • R. M. Curwen, A. Blake, R. Cipolla

   Pages 29-35

7. Supervised Segmentation Using a Multiresolution Data Representation

   • Isaac Ng, J. Kittler, J. Illingworth

   Pages 36-44

8. 3D Grouping by Viewpoint Consistency Ascent

   • L. Du, G. D. Sullivan, K. D. Baker

   Pages 45-53

9. A Trainable Method of Parametric Shape Description

   • T. F. Cootes, D. H. Cooper, C. J. Taylor, J. Graham

   Pages 54-61

10. Using Projective Invariants for Constant Time Library Indexing in Model Based Vision

    • C. A. Rothwell, A. Zisserman, D. A. Forsyth, J. L. Mundy

    Pages 62-70

11. Invariants of a Pair of Conics Revisited

    • Long Quan, Patrick Gros, Roger Mohr

    Pages 71-77

12. A Modal Approach to Feature-based Correspondence

    • Larry S. Shapiro, J. Michael Brady

    Pages 78-85

13. A method of obtaining the relative positions of 4 points from 3 perspective projections

    • H. Christopher Longuet-Higgins

    Pages 86-94

14. Properties of Local Geometric Constraints

    • Alistair J. Bray, Vaclav Hlavac

    Pages 95-103

15. Texture Boundary Detection — A Structural Approach

    • Wen Wen, Richard J. Fryer

    Pages 104-110

16. The Inference of Structure in Images using Multi-local Quadrature Filters

    • K. Langley, T. J. Atherton

    Pages 111-117

17. Low-level Grouping of Straight Line Segments

    • A. Etemadi, J.-P. Schmidt, G. Matas, J. Illingworth, J. Kittler

    Pages 118-126

18. Connective Hough Transform

    • Shiu Yin K. Yuen

    Pages 127-135

19. Ellipse Detection and Matching with Uncertainty

    • Tim Ellis, Ahmed Abbood, Beatrice Brillault

    Pages 136-144

20. Cooperating motion processes

    • P. H. S. Torr, T. Wong, D. W. Murray, A. Zisserman

    Pages 145-150

Lewis Carroll once wrote a story about a king who wanted a very accurate map of his kingdom. The king had a pathologically fastidious eye for detail and consequently decided that the map was to be produced at a scale of 1:1. The scribes dutifully set to and, in time, the map was made. The map carried details of every tree, every rock and every blade of grass throughout the entire land. The problem occurred when they tried to use -it. First of all, the map was extraordinarily difficult to open out and line up with the countryside. Its sheer bulk meant that it took whole armies to carry it and a great host of bureaucrats and technicians to maintain the information. Such was the detail of the map that as soon as the wind blew strongly, whole sections needed to be redrawn. What was worse was that all the farmers protested because the map completely cut out the light from the sun and all the crops died. Eventually the howls of protest became so strong that the king was forced to take action. He did away with the old paper copy and decided to use the kingdom itself as the map. All lived happily ever after. There are, at least, two morals to this tale. First, you are almost certainly doomed to failure if you do not get the representation of the problem right.

• 3D
• Hough transform
• Stereo
• Textur
• algorithms
• cognition
• computer vision
• genetic algorithms
• image processing
• knowledge
• machine vision
• modeling
• object recognition
• robot
• shading

• The Turing Institute George House, Glasgow, UK

  Peter Mowforth

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