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Table of contents
List of Figures
List of Tables
1 Introduction
1.1 Context
1.2 Challenges
1.3 Thesis objectives
1.4 Thesis outline
1.5 List of publications
2 Related work
2.1 Introduction
2.2 Datasets
2.3 Closed world approaches
2.3.1 Representation learning
2.3.2 Metric Learning
2.3.3 Neural networks
2.3.4 Sparse representations
2.3.5 Re-ranking methods
2.4 Generalizing person re-identication
2.4.1 Identity Inference
2.4.2 Group-based verication
2.4.3 Detection and Re-Identication
2.4.4 Drone based
2.5 Evaluation measures
2.5.1 Closed world measures
2.5.2 Open world measures
2.6 Conclusion
2.7 Position of our work
3 COPReV
3.1 Motivation
3.1.1 Closed world re-identication
3.1.2 From closed world re-id to open world detection and re-id
3.1.3 Existing closed world re-id approaches used in open world re-id
3.1.4 Existing open world re-id approaches
3.2 COPReV
3.2.1 Overview
3.2.2 Problem notations
3.2.3 Mathematical formulation
3.2.4 Optimization
3.3 Experimental results
3.3.1 Feature extraction
3.3.2 Implementation details
3.3.3 Datasets and Re-ID scenarios
3.3.4 Precision about the evaluations
3.3.5 Evaluation on closed world re-id scenario
3.3.6 Evaluation on open world re-id scenario
3.3.7 Discussion on the evaluation measures and practical uses
3.3.8 Evaluation on the verication task
3.3.9 About the initialization
3.3.10 Robustness to unbalanced data
3.4 Conclusion
4 Sparse representations with enhanced collaboration
4.1 Preliminaries
4.1.1 Notations: training and testing data
4.1.2 Notations: sparse coding
4.1.3 Features prerequisites
4.2 Collaborative versus non collaborative sparse coding
4.2.1 Non collaborative sparse coding of probe elements
4.2.2 Collaborative sparse coding of probe elements
4.2.3 Comparison of non collaborative and collaborative sparse coding
4.3 Collaboration enhanced sparse coding for open world re-id
4.3.1 Enhanced collaboration for open world re-identication
4.3.2 Additional dictionary D
4.3.3 A method also relevant for person verication
4.3.4 About the exploitation of multi-shot data
4.4 Experimental results
4.4.1 Implementation details and feature extraction
4.4.2 Datasets, training and testing sets, testing protocols, evaluation
4.4.3 Evaluation on closed and open world re-identication tasks
4.4.4 Evaluation on the person verication task
4.5 Conclusion
5 Bidirectional Sparse Representations
5.1 Dierence between sparse coding of probe and gallery elements
5.1.1 Known and undetermined identities
5.1.2 Availability of gallery and probe data
5.1.3 Final goal
5.2 Reverse direction: sparse coding of gallery elements
5.2.1 Sparse representation of gallery elements
5.2.2 Choice of the additional dictionaries
5.3 Ranking of gallery identities, meaning of the residual errors
5.4 Combination of both representations
5.5 Complexity
5.6 Experimental results
5.6.1 Evaluation on closed and open world re-identication tasks
5.6.2 In uence of the choice of the additional dictionaries
5.6.3 In uence of the number of probe identities simultaneously available
5.6.4 Evaluation on the person verication task
5.7 Conclusion
6 Conclusion and Perspectives
6.1 Conclusion
6.2 Perspectives
6.2.1 Design adapted features for sparse coding approaches .
6.2.2 Adapt the sparse coding framework to multi-camera scenarios
6.2.3 Learn the additional dictionaries in the reverse direction sparse coding
6.2.4 Learn the additional dictionary in the direct direction sparse coding
6.2.5 Complexity and speed considerations for huge datasets
6.2.6 A better use of simultaneously appearing people
6.2.7 Generalize even more the re-identication task: dynamic set of identities
7 Resume en francais
7.1 Introduction
7.2 Etat de l’art
7.3 COPReV
7.3.1 Presentation de la methode
7.3.2 Resultats experimentaux
7.3.3 Conclusion
7.4 Representations parcimonieuses avec une collaboration elargie
7.4.1 Presentation de la methode
7.4.2 Resultats experimentaux
7.4.3 Conclusion
7.5 Representation collaborative bidirectionnelle
7.5.1 Presentation de la methode
7.5.2 Resultats experimentaux
7.5.3 Conclusion
7.6 Conclusion et perspectives
7.6.1 Conclusion
7.6.2 Perspectives
Bibliography
