Dense Image Correspondences for Computer Vision

Ce Liu

ISBN 10: 3319359142 / ISBN 13: 9783319359144

Verlag: Springer International Publishing, Springer International Publishing, 2016

Beschreibung

Druck auf Anfrage Neuware - Printed after ordering - This book describes the fundamental building-block of many new computer vision systems: dense and robust correspondence estimation. Dense correspondence estimation techniques are now successfully being used to solve a wide range of computer vision problems, very different from the traditional applications such techniques were originally developed to solve. This book introduces the techniques used for establishing correspondences between challenging image pairs, the novel features used to make these techniques robust, and the many problems dense correspondences are now being used to solve. The book provides information to anyone attempting to utilize dense correspondences in order to solve new or existing computer vision problems. The editors describe how to solve many computer vision problems by using dense correspondence estimation. Finally, it surveys resources, code and data, necessary for expediting the development of effective correspondence-based computer vision systems.

Bestandsnummer des Verkäufers 9783319359144

Bibliografische Details

• Titel: Dense Image Correspondences for Computer Vision
• Verlag: Springer International Publishing, Springer International Publishing
• Erscheinungsjahr: 2016
• Sprache: Englisch
• ISBN-10: 3319359142
• ISBN-13: 9783319359144
• Einband: Taschenbuch
• Zustand: Neu
• Abmessungen: 235B x 155 H x 17 T Millimeter Breite: 235 mm, Höhe: 155 mm, Tiefe: 17 mm
• Gewicht: 470 Gramm

Über diesen Titel

Inhaltsangabe

This book describes the fundamental building-block of many new computer vision systems: dense and robust correspondence estimation. Dense correspondence estimation techniques are now successfully being used to solve a wide range of computer vision problems, very different from the traditional applications such techniques were originally developed to solve. This book introduces the techniques used for establishing correspondences between challenging image pairs, the novel features used to make these techniques robust, and the many problems dense correspondences are now being used to solve. The book provides information to anyone attempting to utilize dense correspondences in order to solve new or existing computer vision problems. The editors describe how to solve many computer vision problems by using dense correspondence estimation. Finally, it surveys resources, code and data, necessary for expediting the development of effective correspondence-based computer vision systems.

Über die Autorin bzw. den Autor

Prof. Tal Hassner is a faculty member of the Department of Mathematics and Computer Science, The Open University of Israel, Israel. Ce Liu is a Researcher with Google.