Technical Papers
Points
Tuesday, 23 July 10:45 AM - 12:15 PM
Session Chair: Tamy Boubekeur, Telecom Paris Tech
Tuesday, 23 July 10:45 AM - 12:15 PM
Session Chair: Tamy Boubekeur, Telecom Paris Tech
A resampling approach to process a noisy and possibly outlier-ridden point set in an edge-aware manner.
Hui Huang
Shenzhen Institute of Advanced Technology
Shihao Wu
South China University of Technology
Minglun Gong
Memorial University of Newfoundland
Daniel Cohen-Or
Tel-Aviv University
Uri Ascher
The University of British Columbia
Hao Zhang
Simon Fraser University
This denoising algorithm for triangulated models based on L_0 minimization maximizes the flat regions and gradually removes noise while preserving sharp features. The process includes building a differential operator for arbitrary triangle meshes that is robust with respect to degenerate triangulations.
Lei He
Texas A&M University
Scott Schaefer
Texas A&M University
An L1-medial skeleton construction algorithm that can be directly applied to an unoriented raw point scan with significant noise, outliers, and large areas of missing data.
Hui Huang
Shenzhen VisuCA Key Lab, Simon Fraser University
Shihao Wu
South China University of Technology
Daniel Cohen-Or
Tel-Aviv University
Minglun Gong
Memorial University of Newfoundland
Hao Zhang
Simon Fraser University
Guiqing Li
South China University of Technology
Baoquan Chen
Shenzhen VisuCA Key Lab, Simon Fraser University
A complete system for semantically segmenting and reconstructing 3D models from point clouds of residential scenes. The paper proposes an efficient decomposition and reconstruction algorithm for low-rise houses with incomplete and noisy data.
Hui Lin
University of Kentucky
Jizhou Gao
University of Kentucky
Yu Zhou
Nanjing University
Guiliang Lu
Nanjing University
Mao Ye
University of Kentucky
Chenxi Zhang
University of Kentucky
Ligang Liu
University of Science and Technology of China
Ruigang Yang
University of Kentucky