Recently, the emergence of 3D cameras, 3D scanners and various cameras including Lidar is expected to promote various 3D media applications such as AR, VR and autonomous mobile vehicles. The 3D media can be recently realized by not only 2D pixel and depth information but also points with texture and geometry information. In particular, 3D point cloud data is consisted of hundreds of thousands to millions of 3D points, and thus dramatically increases its data size compared to 2D media data, which brings up the development of an efficient encoding/decoding technology. Also, it is required to develop a scalability function such as Level of Detail (LoD) for both an effective service with different bandwidths, devices and Region of Interest (RoI). In this paper, we propose a new LoD quality parameter considering characteristics of 3D point cloud contents instead of bitrate change based on a video codec in MPEG Video-based Point Cloud Compression (V-PCC). Therefore, the use of LoD table proposed in this paper is confirmed to generate 3D point cloud contents with different point density.
The point cloud is a medium that visualizes various information by placing a point having a color value and a geometry value in a three-dimensional space. The point cloud uses dozens and millions of points for visualization of information, and the key point of commercialization of this point cloud video is to efficiently compress a large amount of information of point cloud and transmit it to users. Currently, MPEG V-PCC is conducting dynamic point cloud compression research using the 2D video codec, where motion estimation is conducted in terms of 2D video sequences. Thus, there is a limitation in estimating the motion in 3D point cloud contents. In this paper, we propose the method to use the 3D motion for point cloud video compression. The proposed technology achieves efficient compression rate and improves accuracy in lossy compression.
Conference Committee Involvement (3)
Ultra-High-Definition Imaging Systems III
3 February 2020 | San Francisco, California, United States
Ultra-High-Definition Imaging Systems II
2 February 2019 | San Francisco, California, United States
Ultra-High-Definition Imaging Systems
31 January 2018 | San Francisco, California, United States