Human Re-Identification

Nonfiction, Computers, Advanced Computing, Artificial Intelligence, Application Software, Computer Graphics, General Computing
Cover of the book Human Re-Identification by Ziyan Wu, Springer International Publishing
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Author: Ziyan Wu ISBN: 9783319409917
Publisher: Springer International Publishing Publication: September 8, 2016
Imprint: Springer Language: English
Author: Ziyan Wu
ISBN: 9783319409917
Publisher: Springer International Publishing
Publication: September 8, 2016
Imprint: Springer
Language: English

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.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

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