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Person Re-Identification

Overview of attention for book
Cover of 'Person Re-Identification'

Table of Contents

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    Book Overview
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    Chapter 1 The Re-identification Challenge
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    Chapter 2 Discriminative Image Descriptors for Person Re-identification
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    Chapter 3 SDALF: Modeling Human Appearance with Symmetry-Driven Accumulation of Local Features
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    Chapter 4 Re-identification by Covariance Descriptors
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    Chapter 5 Attributes-Based Re-identification
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    Chapter 6 Person Re-identification by Attribute-Assisted Clothes Appearance
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    Chapter 7 Person Re-identification by Articulated Appearance Matching
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    Chapter 8 One-Shot Person Re-identification with a Consumer Depth Camera
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    Chapter 9 Group Association: Assisting Re-identification by Visual Context
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    Chapter 10 Evaluating Feature Importance for Re-identification
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    Chapter 11 Learning Appearance Transfer for Person Re-identification
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    Chapter 12 Mahalanobis Distance Learning for Person Re-identification
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    Chapter 13 Dictionary-Based Domain Adaptation Methods for the Re-identification of Faces
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    Chapter 14 From Re-identification to Identity Inference: Labeling Consistency by Local Similarity Constraints
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    Chapter 15 Re-identification for Improved People Tracking
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    Chapter 16 Benchmarking for Person Re-identification
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    Chapter 17 Person Re-identification: System Design and Evaluation Overview
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    Chapter 18 People Search with Textual Queries About Clothing Appearance Attributes
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    Chapter 19 Large-Scale Camera Topology Mapping: Application to Re-identification
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    Chapter 20 Scalable Multi-camera Tracking in a Metropolis
Attention for Chapter 4: Re-identification by Covariance Descriptors
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Citations

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Summary Dimensions citations
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Chapter title
Re-identification by Covariance Descriptors
Chapter number 4
Book title
Person Re-Identification
Published by
Springer, London, January 2014
DOI 10.1007/978-1-4471-6296-4_4
Book ISBNs
978-1-4471-6295-7, 978-1-4471-6296-4
Authors

Sławomir Bąk, François Brémond

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 11%
Unknown 8 89%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 22%
Student > Ph. D. Student 2 22%
Student > Master 2 22%
Student > Doctoral Student 2 22%
Unspecified 1 11%
Other 0 0%
Readers by discipline Count As %
Computer Science 6 67%
Unspecified 1 11%
Engineering 1 11%
Unknown 1 11%

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