The cookie-related information is fully under our control. These cookies are not used for any purpose other than those described here. Unibo policy
PCA is a classical method to learn common information of a sequence of images. Especially in video analysis, this requires the computation of the (thin) SVD of large matrices. We present a method, based on an efficient SVD computation for augmented matrices, that allows to adapt the number of relevant singular vectors while analyzing a sequence of images. This technique allows the detection of moving elements in surveillance videos with varying background.
This presentation is part of Minisymposium “MS2 - Interpolation and Approximation Methods in Imaging (4 parts)”
organized by: Alessandra De Rossi (University of Torino) , Costanza Conti (University of Firenze) , Francesco Dell'Accio (University of Calabria) .