Computer Vision Metrics Survey, Taxonomy, and Analysis /
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...
保存先:
| 第一著者: | |
|---|---|
| 団体著者: | |
| フォーマット: | 電子媒体 eBook |
| 言語: | 英語 |
| 出版事項: |
Berkeley, CA :
Apress : Imprint: Apress,
2014.
|
| 版: | 1st ed. 2014. |
| 主題: | |
| オンライン･アクセス: | Link to Metadata |
| タグ: |
タグ追加
タグなし, このレコードへの初めてのタグを付けませんか!
|
| 要約: | 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. |
|---|---|
| 物理的記述: | XXXI, 508 p. 216 illus. online resource. |
| ISBN: | 9781430259305 |
| DOI: | 10.1007/978-1-4302-5930-5 |
| アクセス: | Open Access |