Logo

Computer Vision Metrics: Survey, Taxonomy, and Analysis

Large book cover: Computer Vision Metrics: Survey, Taxonomy, and Analysis

Computer Vision Metrics: Survey, Taxonomy, and Analysis
by

Publisher: Springer
ISBN/ASIN: 1430259299
ISBN-13: 9781430259299
Number of pages: 498

Description:
Provides an extensive survey and analysis of over 100 current and historical feature description and machine vision methods, with a detailed taxonomy for local, regional and global features. This book provides necessary background to develop intuition about why interest point detectors and feature descriptors actually work, how they are designed, with observations about tuning the methods for achieving robustness and invariance targets for specific applications.

Home page url

Download or read it online for free here:
Download link
(16MB, PDF)

Similar books

Book cover: Modern Robotics with OpenCVModern Robotics with OpenCV
by - Science Publishing Group
This book is written to provide an introduction to intelligent robotics using OpenCV. It is intended for a first course in robot vision and covers modeling and implementation of intelligent robot. Written for student and hobbyist.
(8349 views)
Book cover: Computer Vision: Algorithms and ApplicationsComputer Vision: Algorithms and Applications
by - Springer
The book emphasizes basic techniques that work under real-world conditions, not the esoteric mathematics without practical applicability. The text is suitable for a senior-level undergraduates in computer science and electrical engineering.
(27683 views)
Book cover: Visual ReconstructionVisual Reconstruction
by - The MIT Press
Visual Reconstruction presents a unified and highly original approach to the treatment of continuity in vision. The book introduces two new concepts: the weak continuity constraint and the graduated nonconvexity algorithm.
(11848 views)
Book cover: Stereo VisionStereo Vision
by - InTech
The book comprehensively covers almost all aspects of stereo vision. In addition reader can find topics from defining knowledge gaps to the state of the art algorithms as well as current application trends of stereo vision.
(14280 views)