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Open Access 2014 | Open Access | Buch

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Computer Vision Metrics

Survey, Taxonomy, and Analysis

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SUCHEN

Über dieses Buch

Computer Vision Metrics 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. The survey is broader than it is deep, with over 540 references provided to dig deeper. The taxonomy includes search methods, spectra components, descriptor representation, shape, distance functions, accuracy, efficiency, robustness and invariance attributes, and more. Rather than providing ‘how-to’ source code examples and shortcuts, this book provides a counterpoint discussion to the many fine opencv community source code resources available for hands-on practitioners.

Inhaltsverzeichnis

Frontmatter

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Chapter 1. Image Capture and Representation
Abstract
“The changing of bodies into light, and light into bodies, is very conformable to the course of Nature, which seems delighted with transmutations.”
Scott Krig

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Chapter 2. Image Pre-Processing
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Chapter 3. Global and Regional Features
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Chapter 4. Local Feature Design Concepts, Classification, and Learning
Abstract
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Scott Krig

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Chapter 5. Taxonomy of Feature Description Attributes
Abstract
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Chapter 6. Interest Point Detector and Feature Descriptor Survey
Abstract
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Scott Krig

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Chapter 7. Ground Truth Data, Content, Metrics, and Analysis
Abstract
■■■ Abstract is required for online version. Please provide if necessary.
Scott Krig

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Chapter 8. Vision Pipelines and Optimizations
Abstract
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Scott Krig

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Chapter 9. Synthetic Feature Analysis
Abstract
This appendix provides analysis of several common detectors against the synthetic feature alphabets described in Chapter 7. The complete source code, shell scripts, and the alphabet image sets are available from Springer Apress at: http://www.apress.com/source-code/ComputerVisionMetrics
Scott Krig

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Chapter 10. Survey of Ground Truth Datasets
Abstract
Table B-1 is a brief survey of public domain datasets in various categories, in no particular order. Note that many of the public domain datasets are freely available from universities and government agencies.
Scott Krig

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Chapter 11. Imaging and Computer Vision Resources
Abstract
This appendix contains a list of some resources for computer vision and imaging, including commercial products, open-source projects, organizations, and standards bodies.
Scott Krig

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Chapter 12. Extended SDM Metrics
Abstract
Figure D-1 provides a visualization of image texture using SDM’s.
Scott Krig

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Bibliography
Abstract
1. Bajcsy, R. "Computer Description of Textured Surfaces." International Conference on Artificial Intelligence, 1973.
Scott Krig
Backmatter
Metadaten
Titel
Computer Vision Metrics
verfasst von
Scott Krig
Copyright-Jahr
2014
Verlag
Apress
Electronic ISBN
978-1-4302-5930-5
Print ISBN
978-1-4302-5929-9
DOI
https://doi.org/10.1007/978-1-4302-5930-5

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