Laplacian Eigenmaps for dimensionality reduction and data representation
Neural Computation
Tracking Across Multiple Cameras With Disjoint Views
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Robust Histogram Construction from Color Invariants for Object Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Spatiograms versus Histograms for Region-Based Tracking
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Person Reidentification Using Spatiotemporal Appearance
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Human appearance modeling for matching across video sequences
Machine Vision and Applications
A tutorial on spectral clustering
Statistics and Computing
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part II
Detection of loitering individuals in public transportation areas
IEEE Transactions on Intelligent Transportation Systems
Re-identification of visual targets in camera networks: a comparison of techniques
ICIAR'11 Proceedings of the 8th international conference on Image analysis and recognition - Volume Part I
Exploiting dissimilarity representations for person re-identification
SIMBAD'11 Proceedings of the First international conference on Similarity-based pattern recognition
3DPeS: 3D people dataset for surveillance and forensics
J-HGBU '11 Proceedings of the 2011 joint ACM workshop on Human gesture and behavior understanding
Appearance-based people recognition by local dissimilarity representations
Proceedings of the on Multimedia and security
Fast person re-identification based on dissimilarity representations
Pattern Recognition Letters
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This paper presents a solution of the appearance-based people re-identification problem in a surveillance system including multiple cameras with different fields of vision. We first utilize different color-based features, combined with several illuminant invariant normalizations in order to characterize the silhouettes in static frames. A graph-based approach which is capable of learning the global structure of the manifold and preserving the properties of the original data in a lower dimensional representation is then introduced to reduce the effective working space and to realize the comparison of the video sequences. The global system was tested on a real data set collected by two cameras installed on board a train. The experimental results show that the combination of color-based features, invariant normalization procedures and the graph-based approach leads to very satisfactory results.