Human Re-Identification [electronic resource] /
Wu, Ziyan.author.
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.
Includes index.
The Problem of Human re-identification -- Features and Signatures -- Multi-Object Tracking -- Surveillance Camera and its Calibration -- Calibrating a Surveillance Camera Network -- Learning Viewpoint Invariant Signatures -- Learning Subject-Discriminative Features -- Dimension Reduction with Random Projections -- Sample Selection for Multi-shot Human Reidentification -- Conclusions and Future Work.
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.
Optical data processing.
Artificial intelligence.
Multimedia information systems.
Computer communication systems.
Image Processing and Computer Vision.
Artificial Intelligence.
Multimedia Information Systems.
Computer Communication Networks.