- Covers every aspect of an end-to-end real-world human re-identification system
- Analyzes and summarizes factors of challenges, risks and uncertainties from practical computer vision applications
- Extensive evaluation and benchmarking on mainstream human re-identification algorithms and datasets
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- About this book
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This book covers aspects of human re-identification problems related to computer vision and machine learning. Working from a practical perspective, it introduces novel algorithms and designs for human re-identification that bridge the gap between research and reality. The primary focus is on building a robust, reliable, distributed and scalable smart surveillance system that can be deployed in real-world scenarios. This book also includes detailed discussions on pedestrian candidates detection, discriminative feature extraction and selection, dimension reduction, distance/metric learning, and decision/ranking enhancement.This book is intended for professionals and researchers working in computer vision and machine learning. Advanced-level students of computer science will also find the content valuable.
- Table of contents (10 chapters)
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The Problem of Human Re-Identification
Pages 3-11
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Features and Signatures
Pages 13-21
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Multi-object Tracking
Pages 23-26
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Surveillance Camera and Its Calibration
Pages 29-39
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Calibrating a Surveillance Camera Network
Pages 41-53
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Table of contents (10 chapters)
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Bibliographic Information
- Bibliographic Information
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- Book Title
- Human Re-Identification
- Authors
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- Ziyan Wu
- Series Title
- Multimedia Systems and Applications
- Copyright
- 2016
- Publisher
- Springer International Publishing
- Copyright Holder
- Springer International Publishing Switzerland
- eBook ISBN
- 978-3-319-40991-7
- DOI
- 10.1007/978-3-319-40991-7
- Hardcover ISBN
- 978-3-319-40990-0
- Softcover ISBN
- 978-3-319-82235-8
- Edition Number
- 1
- Number of Pages
- XV, 104
- Number of Illustrations
- 40 b/w illustrations
- Topics
