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Geometry-Corrected Geodesic Motion Modeling with Per-Frame Camera Motion for 360-Degree Video Compression
Andy Regensky, André Kaup
The large amounts of data associated with 360-degree video require highly effective compression techniques for efficient storage and distribution. The development of improved motion models for 360-degree motion compensation has shown significant improvements in compression efficiency. A geodesic motion model representing translational camera motion proved to be one of the most effective models. In this paper, we propose an improved geometry-corrected geodesic motion model that outperforms the state of the art at reduced complexity. We additionally propose the transmission of per-frame camera motion information, where prior work assumed the same camera motion for all frames of a sequence. Our approach yields average Bj{\o}ntegaard Delta rate savings of 2.27% over H.266/VVC, outperforming the original geodesic motion model by 0.32 percentage points at reduced computational complexity.
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