VIP Lab’s paper accepted to IEEE Transactions on Pattern Analysis and Machine Intelligence
UNIST ECE student Jae-Seong Yun and Prof. Jae-Young Sim’s paper has been accepted to IEEE Transactions on Pattern Analysis and Machine Intelligence (IF: 17.730).
Large-scale 3D point clouds (LS3DPCs) captured by terrestrial LiDAR (Light Detection And Ranging) scanners often include virtual points which are generated by glass reflection. The virtual points may degrade the performance of various computer vision techniques when applied to LS3DPCs. In this paper, we first propose a virtual point removal algorithm for LS3DPCs with multiple glass planes.
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) publishes papers on subjects related to computer vision and image understanding, all traditional areas of pattern analysis and recognition, and selected areas of machine intelligence, with a particular emphasis on machine learning for pattern analysis.
According to the Journal Citation Reports (JCR), IEEE TPAMI has 2018 impact factor of 17.730 which ranks 1st among 265 journals in the field of Electrical and Electronic Engineering and ranks 1st among 133 journals in the field of Computer Science and Artificial Intelligence.
For more information, please refer to the publication details:
Authors: Jae-Seong Yun and Jae-Young Sim (corresponding author)
Title: Virtual point removal for large-scale 3D point clouds with multiple glass planes
Journal: IEEE Transactions on Pattern Analysis and Machine Intelligence