Journal of Artificial Intelligence and Data Science, vol.2, no.1, pp.1-4, 2022 (Peer-Reviewed Journal)
Burgeoning advances in 3 Dimensional (3D) video technologies can only be emphasized by considering the impact of these technologies on the perception of 3D videos from a user point of view. It is a fact that enabling this can be achieved by considering key factors characterizing the nature of a 3D video. Under the light of this fact, spatial resolution and perceptually significant depth levels, which are two effective factors for the depth perception of a 3D video, are used to develop a Reduced Reference (RR) model for the depth perception prediction of a 3D video. While determining the perceptually significant features, bilateral filter is exploited. Structural SIMilarity metric (SSIM) is used to predict the depth perception enabled considering the degradation in the perceptually important features of depth maps having different spatial resolutions. The performance results of the developed model prove that it is quite effective in the depth perception prediction of a 3D video.