People re-identification by graph kernels methods
GbRPR'11 Proceedings of the 8th international conference on Graph-based representations in pattern recognition
Person re-identification by descriptive and discriminative classification
SCIA'11 Proceedings of the 17th Scandinavian conference on Image analysis
A graph-kernel method for re-identification
ICIAR'11 Proceedings of the 8th international conference on Image analysis and recognition - Volume Part I
A multiple component matching framework for person re-identification
ICIAP'11 Proceedings of the 16th international conference on Image analysis and processing - Volume Part II
Exploiting dissimilarity representations for person re-identification
SIMBAD'11 Proceedings of the First international conference on Similarity-based pattern recognition
Boosted human re-identification using Riemannian manifolds
Image and Vision Computing
Appearance-based people recognition by local dissimilarity representations
Proceedings of the on Multimedia and security
Person re-identification in crowd
Pattern Recognition Letters
Fast person re-identification based on dissimilarity representations
Pattern Recognition Letters
Part-based spatio-temporal model for multi-person re-identification
Pattern Recognition Letters
Relaxed pairwise learned metric for person re-identification
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VI
Local descriptors encoded by fisher vectors for person re-identification
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume Part I
Symmetry-driven accumulation of local features for human characterization and re-identification
Computer Vision and Image Understanding
On-the-fly feature importance mining for person re-identification
Pattern Recognition
Editor's Choice Article: A survey of approaches and trends in person re-identification
Image and Vision Computing
Features accumulation on a multiple view oriented model for people re-identification
3DOR '13 Proceedings of the Sixth Eurographics Workshop on 3D Object Retrieval
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In many surveillance systems there is a requirement todetermine whether a given person of interest has alreadybeen observed over a network of cameras. This paperpresents two approaches for this person re-identificationproblem. In general the human appearance obtained in onecamera is usually different from the ones obtained in anothercamera. In order to re-identify people the human signatureshould handle difference in illumination, pose andcamera parameters. Our appearance models are based onhaar-like features and dominant color descriptors. The AdaBoostscheme is applied to both descriptors to achieve themost invariant and discriminative signature. The methodsare evaluated using benchmark video sequences with differentcamera views where people are automatically detectedusing Histograms of Oriented Gradients (HOG). The reidentificationperformance is presented using the cumulativematching characteristic (CMC) curve.