Fast multi-view video plus depth coding with hierarchical bi-prediction

Abstract

This research work is partially funded by STEPS-Malta and partially by the EU–ESF 1.25.The Multi-view Video Coding (MVC) standard was developed for efficient encoding of multi-view videos. Part of it requires the calculation of both disparity and motion estimations using a bi-prediction structure. These estimations involve an exhaustive search for the optimal compensation vectors from multiple forward and backward reference frames which, while being very efficient in terms of compression, results in high computational costs. This paper proposes a solution that utilizes the multi-view geometry along with the available depth data, to calculate more accurate predictors for both motion and disparity estimations, and for both directions of the prediction structure. Simulation results demonstrate that this technique is reliable enough to allow a substantial reduction in the search areas in all the reference frames. This in turn results in a significant speed-up gain of 3.2 times with a negligible influence on the coding efficiency, while encoding both the color and the depth MVVs.peer-reviewe

Low complexity disparity estimation for immersive 3D video transmission

“…This fast disparity estimation technique can also be used with our fast geometric motion estimation techniques, proposed in [19][20][21], to finally obtain a low-computational multi-view video encoder, adequate for low-latency 3DV coding.…”

“…The smallest distortions are normally obtained from the corresponding multi-view areas, as they represent the same object in the viewpoint reference frames [17]. Hence, usually searching only around these similar areas can significantly reduce the exhaustive search and its computational time [9,[18][19][20][21]. These areas can be identified through the multi-view geometry [17] and the average depth value of the current sub-MB to estimate, with the depth values obtained from the depth map MVV.…”