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Human Re-Identification [electronic resource] / by Ziyan Wu.

By: Wu, Ziyan [author.].
Contributor(s): SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Multimedia Systems and Applications: Publisher: Cham : Springer International Publishing : Imprint: Springer, 2016Description: XV, 104 p. 40 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319409917.Subject(s): Computer science | Computer communication systems | Multimedia information systems | Artificial intelligence | Image processing | Computer Science | Image Processing and Computer Vision | Artificial Intelligence (incl. Robotics) | Multimedia Information Systems | Computer Communication NetworksAdditional physical formats: Printed edition:: No titleDDC classification: 006.6 | 006.37 Online resources: Click here to access online
Contents:
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.
In: Springer eBooksSummary: 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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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.

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