Computer Vision : Three-Dimensional Data from Images

Reinhard Klette

ISBN 10: 9813083719 / ISBN 13: 9789813083714

Published by Springer Nature Singapore, Springer, 1998

About this Item

Druck auf Anfrage Neuware - Printed after ordering - This computer vision textbook describes the reconstruction of object surfaces and the analysis of distances between camera and objects. Main topics are static and dynamic stereo analysis, shape from shading, photometric stereo analysis, and structured illumination. The selected procedures, e.g., complex algorithms as Tsai calibration, Frankot-Chellapa depth map generation, or Lee-Rosenfield shape from shading, are discussed at a detailed level such that implementations can follow the given descriptions. Fundamentals are given for these application oriented approaches with respect to camera modeling and calibration, to geometric surface modeling, and to surface reflectance models. New research and laboratory results in shape reconstruction and depth analysis, e.g., based on color images have been included. The text is suitable for graduate courses in computer science, in several engineering disciplines, or in applied mathematics. Theoretical and applied excercises accompany each chapter.

Seller Inventory # 9789813083714

Bibliographic Details

• Title: Computer Vision : Three-Dimensional Data from Images
• Publisher: Springer Nature Singapore, Springer
• Publication Date: 1998
• Language: English
• ISBN 10: 9813083719
• ISBN 13: 9789813083714
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 244W x 170H x 26D millimeters 244 millimeters width by 170 millimeters height by 26 millimeters depth
• Weight: 786 grams

About this title

Synopsis

This computer vision textbook describes the reconstruction of object surfaces and the analysis of distances between camera and objects. Main topics are static and dynamic stereo analysis, shape from shading, photometric stereo analysis, and structured illumination. The selected procedures, e.g., complex algorithms as Tsai calibration, Frankot-Chellapa depth map generation, or Lee-Rosenfield shape from shading, are discussed at a detailed level such that implementations can follow the given descriptions. Fundamentals are given for these application oriented approaches with respect to camera modeling and calibration, to geometric surface modeling, and to surface reflectance models. New research and laboratory results in shape reconstruction and depth analysis, e.g., based on color images have been included. The text is suitable for graduate courses in computer science, in several engineering disciplines, or in applied mathematics. Theoretical and applied excercises accompany each chapter.