Kavli Affiliate: Wei Gao
| First 5 Authors: Fangyu Shen, Wei Gao, , ,
| Summary:
Video-based point cloud compression (V-PCC) has been an emerging compression
technology that projects the 3D point cloud into a 2D plane and uses high
efficiency video coding (HEVC) to encode the projected 2D videos (geometry
video and color video). In this work, we propose a rate control algorithm for
the all-intra (AI) configuration of V-PCC. Specifically, based on the
quality-dependency existing in the projected videos, we develop an optimization
formulation to allocate target bits between the geometry video and the color
video. Furthermore, we design a two-pass method for HEVC to adapt to the new
characteristics of projected videos, which significantly improves the accuracy
of rate control. Experimental results demonstrate that our algorithm
outperforms V-PCC without rate control in R-D performance with just 0.43%
bitrate error.
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