Person Re-identification Using Haar-based and DCD-based Signature

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.