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Guide to 3D Vision Computation

Geometric Analysis and Implementation

Inhalt

This classroom-tested and easy-to-understand textbook/reference describes the state of the art in 3D reconstruction from multiple images, taking into consideration all aspects of programming and implementation. Unlike other computer vision textbooks, this guide takes a unique approach in which the initial focus is on practical application and the procedures necessary to actually build a computer vision system. The theoretical background is then briefly explained afterwards, highlighting how one can quickly and simply obtain the desired result without knowing the derivation of the mathematical detail. Features: reviews the fundamental algorithms underlying computer vision; describes the latest techniques for 3D reconstruction from multiple images; summarizes the mathematical theory behind statistical error analysis for general geometric estimation problems; presents derivations at the end of each chapter, with solutions supplied at the end of the book; provides additional material at anassociated website.

Bibliografische Angaben

Juli 2018, 321 Seiten, Advances in Computer Vision and Pattern Recognition, Englisch
Springer Nature EN
978-3-319-83955-4

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Weitere Titel der Reihe: Advances in Computer Vision and Pattern Recognition

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