Computer Vision Metrics, Survey, Taxonomy and Analysis | Scott K...
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2014-10-12
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BOOKS FOR PROFESSIONALS BY PROFESSIONALS
®
Computer Vision Metrics
Computer Vision Metrics: Survey, Taxonomy, and Analysis provides a technical tour
through computer vision, with a survey of nearly 100 types of local, regional, and
global feature descriptors, blending history of the field with state-of-the-art analysis
of contemporary methods, rather than just another how-to book with source code
shortcuts and performance analysis. Observations are provided to develop intuition
behind the methods and mathematics, interesting questions are raised for future
research rather than providing all the answers, and a Vision Taxonomy is suggested to
draw a conceptual map of the field. Extensive illustrations are included, with over 540
references to the literature in the comprehensive bibliography to dig deeper.
Computer Vision Metrics explores the key questions behind the design and mathematics
of computer vision metrics and feature descriptors, providing a comprehensive survey
and taxonomy of what methods are used, with analysis and observations about why the
methods work. Several 3D depth sensing methods are surveyed including MVS, stereo, and
structured light.
This work focuses on a slice through the field from the view of feature description
metrics, or how to describe, compute, and design the macro-features and micro-features
that make up larger objects in images. The focus is on the pixel-side of the vision pipeline,
with a light introduction to the back-end training, classification, machine learning, and
matching stages.
Computer Vision Metrics is written for engineers, scientists, and academic
researchers in areas including video analytics, scene understanding, machine vision,
face recognition, gesture recognition, pattern recognition, general object analysis, media
processing, and computational photography.
What You’ll Learn:
• Current status, brief history, and future directions for computer vision metrics
• Taxonomy of local binary, gradient & other spectra, shape features,
and basis spaces
• Overview of 2D image sensing, 3D depth sensing, and image preprocessing
• Vision pipeline optimization methods for computer vision applications
• Characterization of ten OpenCV detectors using synthetic feature alphabets
9781430 259299
53999
ISBN 978-1-4302-5929-9
Krig
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资源评论
mzd1949mzd2014-10-26相当于综述性质，较好的总结了计算机视觉方面的基本内容，作为导论性质的读物较好。毕竟是今年的最新版，很及时。- mojotang2017-01-20入门的资料，可以大略研究一下
