Human Re-Identification
Nonfiction, Computers, Advanced Computing, Artificial Intelligence, Application Software, Computer Graphics, General Computing
| 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.
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.
