Nonrigid Registration-Based Progressive Motion Compensation for Point Cloud Geometry Compression

点云 运动补偿 计算机科学 计算机视觉 四分之一像素运动 运动场 运动估计 人工智能 块匹配算法 点集注册 刚性变换 算法 点(几何) 几何学 数学 视频处理 视频跟踪
作者
Yong Shao,Ge Li,Qi Zhang,Wei Gao,Shan Liu
出处
期刊:IEEE Transactions on Geoscience and Remote Sensing [Institute of Electrical and Electronics Engineers]
卷期号:61: 1-14
标识
DOI:10.1109/tgrs.2023.3321289
摘要

There is a critical requirement for efficiently compressing point cloud geometries representing three-dimensional (3D) moving objects in various applications. The Moving Picture Experts Group 3D Graphics coding group (MPEG 3DG) set up an inter-exploration model for geometry-based point cloud compression (G-PCC interEM). However, the block-matching motion compensation scheme with a translational motion model has limited ability to handle dense point clouds with complex local motions. To overcome this problem, we propose a progressive non-rigid motion compensation framework for point cloud geometry compression, where the point cloud registration technique is introduced and tailored with our designed rate-distortion cost. In the coarse-grained stage, a point cloud is represented as deformable point patches, and the patch-wise non-rigid motion estimation task is formulated as a registration-based optimization problem that can be efficiently solved by the majorization-minimization method. In the fine-grained stage, we propose a block-based motion refinement to enhance the estimated motion field in the local region, followed by a multi-hypothesis motion compensation scheme enabling smooth reference reconstruction with patch-wise deformation and block-wise refined motions. Experiments demonstrate our proposed scheme outperforms several competitive platforms in terms of both coding performance and compensation quality. Compared with G-PCC interEM, our proposed framework achieves significant bitrate savings, i.e., 4.71% (32 frames) and 4.22% (200 frames), for point cloud lossless geometry compression.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
2秒前
坚强的广山应助sbc采纳,获得10
2秒前
2秒前
欧阳发布了新的文献求助10
2秒前
寻道图强应助yzj采纳,获得10
3秒前
夏秋双完成签到 ,获得积分10
4秒前
4秒前
蕾0818完成签到,获得积分10
4秒前
一生所爱完成签到,获得积分10
5秒前
6秒前
善良的晓博完成签到,获得积分10
6秒前
6秒前
6秒前
健壮的友安发布了新的文献求助100
8秒前
星辰大海应助欧阳采纳,获得10
8秒前
10秒前
彭佳丽发布了新的文献求助10
11秒前
子不语发布了新的文献求助10
11秒前
俊逸的以山完成签到,获得积分20
12秒前
yyh12138发布了新的文献求助10
12秒前
Yuan完成签到 ,获得积分10
13秒前
15秒前
pphss完成签到,获得积分10
15秒前
潇洒一曲发布了新的文献求助20
16秒前
echo0411完成签到,获得积分10
16秒前
非凡即圣完成签到,获得积分10
17秒前
19秒前
小马甲应助秃顶双马尾采纳,获得10
20秒前
大个应助彭佳丽采纳,获得10
22秒前
hh发布了新的文献求助10
24秒前
26秒前
26秒前
28秒前
西西旺仔完成签到,获得积分10
28秒前
华仔应助lily采纳,获得10
28秒前
28秒前
29秒前
等待的小玉完成签到,获得积分10
31秒前
LALALA发布了新的文献求助10
31秒前
wxz完成签到,获得积分10
32秒前
高分求助中
Manual of Clinical Microbiology, 4 Volume Set (ASM Books) 13th Edition 1000
Teaching Social and Emotional Learning in Physical Education 900
Boris Pesce - Gli impiegati della Fiat dal 1955 al 1999 un percorso nella memoria 500
Chinese-English Translation Lexicon Version 3.0 500
Recherches Ethnographiques sue les Yao dans la Chine du Sud 500
Two-sample Mendelian randomization analysis reveals causal relationships between blood lipids and venous thromboembolism 500
[Lambert-Eaton syndrome without calcium channel autoantibodies] 460
热门求助领域 (近24小时)
化学 材料科学 医学 生物 有机化学 工程类 生物化学 纳米技术 物理 内科学 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 电极 光电子学 量子力学
热门帖子
关注 科研通微信公众号,转发送积分 2398169
求助须知:如何正确求助?哪些是违规求助? 2099517
关于积分的说明 5292559
捐赠科研通 1827348
什么是DOI,文献DOI怎么找? 910829
版权声明 560049
科研通“疑难数据库(出版商)”最低求助积分说明 486879