Joint Geometry and Attribute Upsampling of Point Clouds Using Frequency-Selective Models with Overlapped Support
This addresses the need for high-resolution point clouds in 3D capture applications, but it is incremental as it builds on existing upsampling methods with a novel joint approach.
The paper tackles the problem of upsampling both geometry and attributes (e.g., color) of point clouds for applications like AR/VR and autonomous driving, proposing Frequency-Selective Upsampling (FSU) which achieves best geometry performance in terms of point-to-plane error and angular similarity, and outperforms other color upsampling schemes by 1.9 dB in color PSNR.
With the increasing demand of capturing our environment in three-dimensions for AR/ VR applications and autonomous driving among others, the importance of high-resolution point clouds rises. As the capturing process is a complex task, point cloud upsampling is often desired. We propose Frequency-Selective Upsampling (FSU), an upsampling scheme that upsamples geometry and attribute information of point clouds jointly in a sequential manner with overlapped support areas. The point cloud is partitioned into blocks with overlapping support area first. Then, a continuous frequency model is generated that estimates the point cloud's surface locally. The model is sampled at new positions for upsampling. In a subsequent step, another frequency model is created that models the attribute signal. Here, knowledge from the geometry upsampling is exploited for a simplified projection of the points in two dimensions. The attribute model is evaluated for the upsampled geometry positions. In our extensive evaluation, we evaluate geometry and attribute upsampling independently and show joint results. The geometry results show best performances for our proposed FSU in terms of point-to-plane error and plane-to-plane angular similarity. Moreover, FSU outperforms other color upsampling schemes by 1.9 dB in terms of color PSNR. In addition, the visual appearance of the point clouds clearly increases with FSU.