Overview
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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Details
- ISBN-13: 9783319822358
- ISBN-10: 3319822357
- Publisher: Springer
- Publish Date: April 2018
- Dimensions: 9.21 x 6.14 x 0.26 inches
- Shipping Weight: 0.4 pounds
- Page Count: 104
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