PROJECT TITLE :

View Synthesis Distortion Estimation With a Graphical Model and Recursive Calculation of Probability Distribution

ABSTRACT:

Depth-image-based mostly rendering (DIBR) is often utilized in multiview video applications like free-viewpoint tv. During this paper, we tend to take into account the 2 DIBR algorithms used in the Moving Picture Experts Group read synthesis reference software, and develop a scheme for the encoder to estimate the distortion of the synthesized virtual read at the decoder when the reference texture and depth sequences experience transmission errors such as packet loss. We tend to first develop a graphical model to analyze how random errors in the reference depth image have an effect on the synthesized virtual read. The warping competition rule adopted in the DIBR algorithms is explicitly represented by the graphical model. We have a tendency to then contemplate the case where packet loss occurs to both the encoded texture and depth pictures during transmission and develop a recursive optimal distribution estimation (RODE) technique to calculate the per-pixel texture and depth probability distributions in every frame of the reference views. The RODE is then integrated with the graphical model method to estimate the distortion in the synthesized view caused by packet loss. Experimental results verify the accuracy of the graphical model methodology, the RODE, and also the combined estimation theme.


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