Xuebin Sun

2 accepted papers

2020

A Novel Coding Architecture for LiDAR Point Cloud Sequence

Xuebin Sun, Sukai Wang, Miaohui Wang, Zheng Wang, Ming Liu

RA-L 2020

In this letter, we propose a novel coding architecture for LiDAR point cloud sequences based on clustering and prediction neural networks. LiDAR point clouds are structured, which provides an opportunity to convert the 3D data to a 2D array, represented as range images. Thus, we cast the LiDAR point

Cited by 24 Source ↗Scholar ↗

2019

A Novel Point Cloud Compression Algorithm Based on Clustering

Xuebin Sun, Han Ma, Yuxiang Sun, Ming Liu

RA-L 2019

Due to the enormous volume of point cloud data, transmitting and storing the data requires large bandwidth and storage space. It could be a critical bottleneck, especially in tasks such as autonomous driving. In this letter, we propose a novel point cloud compression algorithm based on clustering. T

Cited by 82 Source ↗Scholar ↗