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• W4226518690 abstract "The state-of-the-art compression method for Light Detection And Ranging (LiDAR) point clouds is the geometry-based point cloud compression (G-PCC) standard developed by Moving Pictures Experts Group immersive media working group (MPEG-I). However, there are currently no rate control algorithms designed specifically for Geometry-based LiDAR point cloud compression (G-LPCC). In this paper, we propose the first frame-level rate control algorithm for G-LPCC. We mainly have the following contributions in our proposed rate control algorithm. First, we model the rate-distortion (R-D) relationship for both the geometry and attribute. As the geometry bitrate is mainly determined by the frame-level geometry quantizer <formula xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink><tex>$Q_G$</tex></formula> , we propose a relationship between the geometry bitrate and <formula xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink><tex>$Q_G$</tex></formula> . In addition, as the attribute bitrate can be influenced by both the attribute quantizer <formula xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink><tex>$Q_A$</tex></formula> and <formula xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink><tex>$Q_G$</tex></formula> , we build a relationship among the attribute bitrate, <formula xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink><tex>$Q_G$</tex></formula> , and <formula xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink><tex>$Q_A$</tex></formula> . Second, we propose a bit allocation algorithm between the geometry and attribute based on the R-D modeling. The <formula xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink><tex>$Q_G$</tex></formula> and <formula xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink><tex>$Q_A$</tex></formula> are modeled into a proper relationship to obtain geometry and attribute bits to achieve good R-D performance. Third, we propose using the point density of LiDAR point clouds to estimate the geometry model parameters. The point density is calculated using the average distance between each point and its nearest neighbor after excluding some noisy points. The proposed rate control algorithm is implemented in the G-PCC reference software. The experimental results show that the proposed rate control algorithm can control the bitrate accurately with satisfactory R-D performance." @default.
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• W4226518690 date "2023-01-01" @default.
• W4226518690 modified "2023-10-14" @default.
• W4226518690 title "Frame-level Rate Control for Geometry-based LiDAR Point Cloud Compression" @default.
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• W4226518690 doi "https://doi.org/10.1109/tmm.2022.3167810" @default.
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