Complexwavelet Transform Cwt Based Video Magnification For 3d Facial Video Identification

Magnifying micro changes in motion and brightness of videos that are unnoticeable by the human visual system have recently been an interesting area to explore. In this paper, we explore this technique in 3D facial video identification, we utilize this technique to identify 3D objects from 2D images. We present a Complex Wavelet Transform CWT, 2D-Dual CWT based technique, to calculate any changes between subsequent video frames of CWT sub-bands at different spatial locations. In this technique, a gradient based method is proposed to determine the orientation of each CWT sub band in addition to the Radon Transform, RT, that is utilized to detect any periodic motion in the video frames. We conducted many simulation results to show that the proposed hybrid technique provides promising results when compared with the existing literature in micro magnification of videos, like steerable pyramids STR or the Riesz Transform based one RT-STR. The proposed technique has been employed to make a distinction between 3D facial object videos and 2D face image videos, as will be demonstrated in our simulation results.