The UNIST Large-Scale 3D Point Clouds (LS3DPC) dataset for virtual point removal consists of 11 large-scale point clouds containing several millions of points with XYZ cartesian coordinates and RGB colors. This UNIST LS3DPC dataset is captured by RIEGL VZ-400 terrestrial LiDAR scanner and Nikon D700 digital camera concurrently. The XYZ cartesian coordinates are measured in meters. You can easily read the point clouds from PCD files using PCL library or pcread function from Matlab.
Large-Scale 3D Point Clouds Examples
All publications using the dataset or any of the derived dataset should cite the following paper:
Jae-Seong Yun, and Jae-Young Sim, “Virtual point removal for large-scale 3D point clouds with multiple glass planes,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 43, no. 2, pp. 729-744, Feb. 2021. [bibtex]
The use of this dataset is governed by the following terms and conditions. Without the expressed permission of the VIP Lab., any of the following will be considered illegal: redistribution, modification, and commercial usage of any of the dataset in any way or form, either partially or in its entirety. For the sake of privacy, images of all subjects in any of the dataset are only allowed for the demonstration in academic publications and presentations. All users of the UNIST LS3DPC dataset agree to indemnify, defend and hold harmless, the VIP Lab. and its officers, employees, and agents, individually and collectively, from any and all losses, expenses, and damages.
This work was supported by the National Research Foundation of Korea (NRF) within the Ministry of Science and ICT (MSIT) under Grant 2017R1A2B4011970.