Abstract
A point cloud visualizes information by placing a voxel with a color value and a position value in a three-dimensional space. Since a point cloud uses hundreds of thousands or millions of points to visualize information, a large number of bits is needed compared to existing 2D media. Therefore, it is essential to compress point data for transmission and storage. The Moving Picture Expert Group (MPEG) is developing a point cloud compression method based on 2D video that takes advantage of the benefits of coding efficiency and the wide adaption of video codecs by various industries. This compression method is called video-based point cloud compression (V-PCC). Generally, video codecs use a compression method that employs a block matching algorithm. Currently, V-PCC is conducted using 2D video codecs, which means that motion information used by V-PCC is obtained from 2D video sequences. Thus, this 2D-based motion information limits the characterization of the motion in terms of 3D-points, which is also disadvantageous to compression efficiency. In this paper, we propose a method for estimating and compensating the motion in terms of a 3D object when compressing a dynamic object point cloud using a conventional video codec. The proposed 3D motion estimation and compensation technology showed higher gain overall in terms of BD-rate and was proven to effectively compress 3D point cloud content on the basis of 3D motion.
Highlights
Conventional 2D images represent objects and scenes as a set of pixels with color values
EXPERIMENTAL RESULTS The performance of the 3D motion estimation and compensation technology proposed in this paper was determined using videobased point cloud compression (V-PCC) reference software v4 [29]
High Efficiency Video Coding (HEVC) was used as the 2D video codec, and the test point cloud sequences called ‘‘Soldier’’, ‘‘Queen’’, ‘‘Longdress’’, ‘‘Red and Black’’ and ‘‘Loot’’ were used under Common Test Conditions (CTC) in V-PCC [30]
Summary
Conventional 2D images represent objects and scenes as a set of pixels with color values. MPEG has started to develop a compression method for dynamic point clouds that uses an existing video codec [8]. In V-PCC, the 2D video codec basically uses a motionsearch-based compression method such as a block matching algorithm [12] This requires that the motion search is conducted only in a projected 2D domain generated in a direction orthogonal to the 3D points. We propose a method for estimating and compensating the motion in terms of a 3D object when compressing a dynamic object point cloud using a conventional video codec. 3D MOTION ESTIMATION AND COMPENSATION As explained, V-PCC performs a compression of dynamic point cloud content using a 2D video codec which allows for a highly reliable and economical compression method.
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