Support vector domain description
Pattern Recognition Letters - Special issue on pattern recognition in practice VI
IEEE Transactions on Pattern Analysis and Machine Intelligence
Estimating the Support of a High-Dimensional Distribution
Neural Computation
Panoramic Appearance Map (PAM) for Multi-camera Based Person Re-identification
AVSS '06 Proceedings of the IEEE International Conference on Video and Signal Based Surveillance
Kernel PCA for novelty detection
Pattern Recognition
Kernels, regularization and differential equations
Pattern Recognition
Graph kernels based on tree patterns for molecules
Machine Learning
Approximate graph edit distance computation by means of bipartite graph matching
Image and Vision Computing
Bridging the Gap Between Graph Edit Distance and Kernel Machines
Bridging the Gap Between Graph Edit Distance and Kernel Machines
People Reidentification in a Camera Network
DASC '09 Proceedings of the 2009 Eighth IEEE International Conference on Dependable, Autonomic and Secure Computing
Bipartite graph matching for computing the edit distance of graphs
GbRPR'07 Proceedings of the 6th IAPR-TC-15 international conference on Graph-based representations in pattern recognition
People re-identification by spectral classification of silhouettes
Signal Processing
Person Re-identification Using Haar-based and DCD-based Signature
AVSS '10 Proceedings of the 2010 7th IEEE International Conference on Advanced Video and Signal Based Surveillance
Performance Evaluation of a People Tracking System on PETS2009 Database
AVSS '10 Proceedings of the 2010 7th IEEE International Conference on Advanced Video and Signal Based Surveillance
Multiple-Shot Person Re-identification by HPE Signature
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
An online kernel change detection algorithm
IEEE Transactions on Signal Processing - Part II
Detection of loitering individuals in public transportation areas
IEEE Transactions on Intelligent Transportation Systems
Editor's Choice Article: A survey of approaches and trends in person re-identification
Image and Vision Computing
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People re-identification using single or multiple camera acquisitions constitutes a major challenge in visual surveillance analysis. The main application of this research field consists to reacquire a person of interest in different non-overlapping locations over different camera views. This paper present an original solution to this problem based on a graph description of each person. In particular, a recently proposed graph kernel is used to apply Principal Component Analysis (PCA) to the graph domain. The method has been experimentally tested on two video sequences from the PETS2009 database.