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9781334537950: Finding Representative Points of Closest Approach for Noisy Curves (Classic Reprint)

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This book explores a novel approach to object recognition by describing objects in terms of their 3D curves. It presents two methods for choosing representative points of closest approach that can be used to efficiently match sets of curves in 3D space, even when the curves are corrupted by noise. The methods are evaluated using computer-generated curves with varying amounts of noise, and the results demonstrate that the centroid method allows better selection of points than quadratic or cubic fits when substantial lengths of the curves can be used, but that a cubic fit of coordinates vs arc length gave better results when relatively short lengths of curve were used. The quadratic fits behaved very badly. The book provides a valuable contribution to the field of object recognition and has applications in data reduction, efficient recognition of 3D objects, and other areas where measuring the spatial separation of sets of curves in 3D space is important.

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9780484278171: Finding Representative Points of Closest Approach for Noisy Curves (Classic Reprint)

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ISBN 10:  0484278177 ISBN 13:  9780484278171
Editorial: Forgotten Books, 2018
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C. Marc Bastuscheck
Publicado por Forgotten Books, 2018
ISBN 10: 133453795X ISBN 13: 9781334537950
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Imagen de archivo

C. Marc Bastuscheck
Publicado por Forgotten Books, 2018
ISBN 10: 133453795X ISBN 13: 9781334537950
Nuevo PAP

Librería: PBShop.store UK, Fairford, GLOS, Reino Unido

Calificación del vendedor: 5 de 5 estrellas Valoración 5 estrellas, Más información sobre las valoraciones de los vendedores

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000. Nº de ref. del artículo: LX-9781334537950

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C. Marc Bastuscheck
Publicado por Forgotten Books, 2018
ISBN 10: 133453795X ISBN 13: 9781334537950
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Librería: Forgotten Books, London, Reino Unido

Calificación del vendedor: 5 de 5 estrellas Valoración 5 estrellas, Más información sobre las valoraciones de los vendedores

Paperback. Condición: New. Print on Demand. This book explores a novel approach to object recognition by describing objects in terms of their 3D curves. It presents two methods for choosing representative points of closest approach that can be used to efficiently match sets of curves in 3D space, even when the curves are corrupted by noise. The methods are evaluated using computer-generated curves with varying amounts of noise, and the results demonstrate that the centroid method allows better selection of points than quadratic or cubic fits when substantial lengths of the curves can be used, but that a cubic fit of coordinates vs arc length gave better results when relatively short lengths of curve were used. The quadratic fits behaved very badly. The book provides a valuable contribution to the field of object recognition and has applications in data reduction, efficient recognition of 3D objects, and other areas where measuring the spatial separation of sets of curves in 3D space is important. This book is a reproduction of an important historical work, digitally reconstructed using state-of-the-art technology to preserve the original format. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in the book. print-on-demand item. Nº de ref. del artículo: 9781334537950_0

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