affine analysis image sequences von shapiro larry (4 Ergebnisse)

Zustand: Very Good. Very Good condition. Good dust jacket. A copy that may have a few cosmetic defects. May also contain light spine creasing or a few markings such as an owner's name, short gifter's inscription or light stamp.

Hardback. Zustand: As New. Series: Distinguished Dissertations in Computer Science. xi 210p large sturdy hardback, navy cloth with blue and yellow jacket, very good condition, minimal wear, jacket a bit sunned, pages clean and bright like new, numerous graphs and diagrams very clear and sharp, a very good copy without names or stamps Language: English Weight (g): 584.

Zustand: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,650grams, ISBN:0521550637.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.