1. A computer-implemented method for processing, by a graphical processor unit (GPU), a plurality of images of a user, the method comprising: selecting, via a device with a central processing unit (CPU) and the GPU, a plurality of features detected by the GPU in a first image of the plurality of images of the user, wherein each feature comprises one or more pixels; in a second image of the plurality of images of the user, searching for the plurality of features selected in the first image; calculating, on the GPU, a variance for each selected feature found in the second image, wherein the variance indicates a degree a portion of the second image varies from a corresponding portion of the first image; storing the calculated variance in a variance file; and performing on the GPU a cross-correlation algorithm, wherein performing the cross-correlation algorithm on the GPU comprises: performing, via the GPU, a fast Fourier transform (FFT) on first and second images from the plurality of images of the user.