Person Re-Identification

1. Front Matter

   Pages i-xviii

   PDF

2. The Re-identification Challenge

   • Shaogang Gong, Marco Cristani, Chen Change Loy, Timothy M. Hospedales

   Pages 1-20

3. Features and Representations

   1. Front Matter

      Pages 21-21

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   2. Discriminative Image Descriptors for Person Re-identification

      • Bingpeng Ma, Yu Su, Frédéric Jurie

      Pages 23-42

   3. SDALF: Modeling Human Appearance with Symmetry-Driven Accumulation of Local Features

      • Loris Bazzani, Marco Cristani, Vittorio Murino

      Pages 43-69

   4. Re-identification by Covariance Descriptors

      • Sławomir Bąk, François Brémond

      Pages 71-91

   5. Attributes-Based Re-identification

      • Ryan Layne, Timothy M. Hospedales, Shaogang Gong

      Pages 93-117

   6. Person Re-identification by Attribute-Assisted Clothes Appearance

      • Annan Li, Luoqi Liu, Shuicheng Yan

      Pages 119-138

   7. Person Re-identification by Articulated Appearance Matching

      • Dong Seon Cheng, Marco Cristani

      Pages 139-160

   8. One-Shot Person Re-identification with a Consumer Depth Camera

      • Matteo Munaro, Andrea Fossati, Alberto Basso, Emanuele Menegatti, Luc Van Gool

      Pages 161-181

   9. Group Association: Assisting Re-identification by Visual Context

      • Wei-Shi Zheng, Shaogang Gong, Tao Xiang

      Pages 183-201

   10. Evaluating Feature Importance for Re-identification

       • Chunxiao Liu, Shaogang Gong, Chen Change Loy, Xinggang Lin

       Pages 203-228

4. Matching and Distance Metric

   1. Front Matter

      Pages 229-229

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   2. Learning Appearance Transfer for Person Re-identification

      • Tamar Avraham, Michael Lindenbaum

      Pages 231-246

   3. Mahalanobis Distance Learning for Person Re-identification

      • Peter M. Roth, Martin Hirzer, Martin Köstinger, Csaba Beleznai, Horst Bischof

      Pages 247-267

   4. Dictionary-Based Domain Adaptation Methods for the Re-identification of Faces

      • Qiang Qiu, Jie Ni, Rama Chellappa

      Pages 269-285

   5. From Re-identification to Identity Inference: Labeling Consistency by Local Similarity Constraints

      • Svebor Karaman, Giuseppe Lisanti, Andrew D. Bagdanov, Alberto Del Bimbo

      Pages 287-307

   6. Re-identification for Improved People Tracking

      • François Fleuret, Horesh Ben Shitrit, Pascal Fua

      Pages 309-330

5. Evaluation and Application

   1. Front Matter

      Pages 331-331

      PDF

   2. Benchmarking for Person Re-identification

      • Roberto Vezzani, Rita Cucchiara

      Pages 333-349

The first book of its kind dedicated to the challenge of person re-identification, this text provides an in-depth, multidisciplinary discussion of recent developments and state-of-the-art methods. Features: introduces examples of robust feature representations, reviews salient feature weighting and selection mechanisms and examines the benefits of semantic attributes; describes how to segregate meaningful body parts from background clutter; examines the use of 3D depth images and contextual constraints derived from the visual appearance of a group; reviews approaches to feature transfer function and distance metric learning and discusses potential solutions to issues of data scalability and identity inference; investigates the limitations of existing benchmark datasets, presents strategies for camera topology inference and describes techniques for improving post-rank search efficiency; explores the design rationale and implementation considerations of building a practical re-identification system.

• 3D Computer Vision
• Active Learning
• Attribute Learning
• Behavioral Biometrics
• Big Data Search
• Context-Aware Recognition
• Data Fusion
• Data Mining
• Distributed Camera Networks
• Human Recognition
• Image Retrieval
• Multi-Camera Tracking
• Multi-Instance Learning
• People Detection
• Person Re-Identification
• Soft Biometrics
• Transfer Learning
• Video Content Analysis
• Visual Surveillance

The book is intended for researchers that work, or want to start working on this research topic. … The book is very interesting and allows having an insight into the problem of person re-identification and its potential applications. It provides a presentation of the current state-of-the-are and recent progress on this topic. I think that researchers who intend to work on re-identification can benefit from reading this book. They will be introduced to the many interesting challenges to be faced.” (Donatello Conte, IAPR Newsletter, Vol. 37 (2), 2015)

• Queen Mary University, London, United Kingdom

  Shaogang Gong

• University of Verona, Italy

  Marco Cristani

• National University of Singapore, Singapore

  Shuicheng Yan

• The Chinese University of Hong Kong, Shatin, Hong Kong SAR

  Chen Change Loy

Dr. Shaogang Gong is a Professor of Visual Computation in the School of Electronic Engineering and Computer Science at Queen Mary University of London, UK. His publications include the successful Springer books Visual Analysis of Behaviour and Video Analytics for Business Intelligence. Dr. Marco Cristani is an Assistant Professor in the Computer Science Department at the University of Verona, Italy. Dr. Shuicheng Yan is an Associate Professor in the Department of Electrical and Computer Engineering at the National University of Singapore. Dr. Chen Change Loy is a Research Assistant Professor in the Department of Information Engineering at the Chinese University of Hong Kong.

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