Table of contents
About this book
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.
video surveillance human re-identification feature extraction metric learning pedestrian recognition machine learning computer vision image understanding object tracking representation learning camera network camera calibration image un-distortion pattern recognition
- DOI https://doi.org/10.1007/978-3-319-40991-7
- Copyright Information Springer International Publishing Switzerland 2016
- Publisher Name Springer, Cham
- eBook Packages Computer Science
- Print ISBN 978-3-319-40990-0
- Online ISBN 978-3-319-40991-7
- Buy this book on publisher's site