Digital Image Correlation (DIC), which consists in registering image pairs to measure displacement fields, can be tailored to analyze image sequences from videos taking advantage of a common reference image. In the present study it is no longer the first image of the sequence but rather a computed image from the entire video. The sought kinematics, which is separated in space and time, offers the opportunity to extract "modes," each of which is a spatial displacement field multiplied by a scalar function of time only. These modes are not chosen a priori but rather computed from a specific formulation of DIC so that they capture the displacements at best. The exploited mathematical technique to achieve this modal representation is a form of Proper Generalized Decomposition (PGD) that makes use of the DIC variational formulation, where both spatial and temporal regularizations can be included. Two image videos acquired with an ultra-high speed camera at 5 and 10 million frames per second are analyzed to illustrate the proposed technique. Very large computation time gains are obtained with no noticeable differences in the kinematic measurements. Moreover, it is shown that motions have a lower complexity, i.e., require less modes, than the direct Proper Orthogonal Decomposition (or Principal Component Analysis)