The development of real-time 3D sensing devices and algorithms (e.g., multiview capturing systems, Time-of-Flight depth cameras, LIDAR sensors), as well as the widespreading of enhanced user applications processing 3D data, have motivated the investigation of innovative and effective coding strategies for 3D point clouds. Several compression algorithms, as well as some standardization efforts, has been proposed in order to achieve high compression ratios and flexibility at a reasonable computational cost. This paper presents a transform-based coding strategy for dynamic point clouds that combines a non-linear transform for geometric data with a linear transform for color data; both operations are region-adaptive in order to fit the characteristics of the input 3D data. Temporal redundancy is exploited both in the adaptation of the designed transform and in predicting the attributes at the current instant from the previous ones. Experimental results showed that the proposed solution obtained a significant bit rate reduction in lossless geometry coding and an improved rate-distortion performance in the lossy coding of color components with respect to state-of-the-art strategies.

中文翻译：

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动态点云的变换编码策略。


实时 3D 传感设备和算法（例如，多视图捕获系统、飞行时间深度相机、LIDAR 传感器）的发展，以及处理 3D 数据的增强型用户应用程序的广泛应用，推动了对创新和技术的研究。 3D 点云的有效编码策略。为了以合理的计算成本实现高压缩比和灵活性，已经提出了几种压缩算法以及一些标准化工作。本文提出了一种基于变换的动态点云编码策略，它将几何数据的非线性变换与颜色数据的线性变换相结合；这两种操作都是区域自适应的，以适应输入 3D 数据的特征。在设计变换的适应和根据先前的属性预测当前时刻的属性时都利用了时间冗余。实验结果表明，相对于最先进的策略，所提出的解决方案在无损几何编码中显着降低了比特率，并在颜色分量有损编码中提高了率失真性能。