Affine Analysis of Image Sequences

Larry S. Shapiro (University of Oxford)

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English

Cambridge University Press
15 September 2005

Applied optics; Computer vision; Image processing

Series: Distinguished Dissertations in Computer Science

Computer vision is a rapidly growing field which aims to make computers 'see' as effectively as humans. In this book Dr Shapiro presents a new computer vision framework for interpreting time-varying imagery. This is an important task, since movement reveals valuable information about the environment. The fully-automated system operates on long, monocular image sequences containing multiple, independently-moving objects, and demonstrates the practical feasibility of recovering scene structure and motion in a bottom-up fashion. Real and synthetic examples are given throughout, with particular emphasis on image coding applications. Novel theory is derived in the context of the affine camera, a generalisation of the familiar scaled orthographic model. Analysis proceeds by tracking 'corner features' through successive frames and grouping the resulting trajectories into rigid objects using new clustering and outlier rejection techniques. The three-dimensional motion parameters are then computed via 'affine epipolar geometry', and 'affine structure' is used to generate alternative views of the object and fill in partial views. The use of all available features (over multiple frames) and the incorporation of statistical noise properties substantially improves existing algorithms, giving greater reliability and reduced noise sensitivity.

By: Larry S. Shapiro (University of Oxford)
Imprint: Cambridge University Press
Country of Publication: United Kingdom
Volume: 10
Dimensions: Height: 245mm, Width: 170mm, Spine: 12mm
Weight: 371g
ISBN: 9780521019781
ISBN 10: 0521019788
Series: Distinguished Dissertations in Computer Science
Pages: 228
Publication Date: 15 September 2005
Audience: Professional and scholarly , Undergraduate
Format: Paperback
Publisher's Status: Active

1. Introduction; 2. Corner extraction and tracking; 3. The affine camera and affine structure; 4. Clustering using maximum affinity spanning trees; 5. Affine epipolar geometry; 6. Outlier rejection in an orthogonal regression framework; 7. Rigid motion from affine epipolar geometry; 8. Affine transfer; 9. Conclusions; Appendices A. Clustering proofs; B. Proofs for epipolar geometry minimisation; C. Proofs for outlier rejection; D. Rotation matrices; E. KdV motion equations; Bibliography; Index.

Reviews for Affine Analysis of Image Sequences

".."".provides an in-depth, thoughtful account of affine imaging and its application to the analysis of image sequences."" M.R.M. Jenkin, Computing Reviews"