3D Photogrammetry Point Cloud Segmentation Using a Model Ensembling Framework-Reference-Cited by-同舟云学术

3D Photogrammetry Point Cloud Segmentation Using a Model Ensembling Framework

Published:2020-11 Issue:6 Volume:34 Page:04020048
ISSN:0887-3801
Container-title:Journal of Computing in Civil Engineering
language:en
Short-container-title:J. Comput. Civ. Eng.

Author:

Chen Meida¹^ORCID,Feng Andrew²,McCullough Kyle³^ORCID,Prasad Pratusha Bhuvana⁴,McAlinden Ryan⁵,Soibelman Lucio⁶^ORCID

Affiliation:

1. Research Associate, Institute for Creative Technologies, Univ. of Southern California, 12015 E. Waterfront Dr., Los Angeles, CA 90094 (corresponding author). ORCID: .

2. Research Scientist, Institute for Creative Technologies, Univ. of Southern California, 12015 E. Waterfront Dr., Los Angeles, CA 90094.

3. Lead Programmer, Institute for Creative Technologies, Univ. of Southern California, 12015 E. Waterfront Dr., Los Angeles, CA 90094. ORCID: .

4. Researcher, Institute for Creative Technologies, Univ. of Southern California, 12015 E. Waterfront Dr., Los Angeles, CA 90094.

5. Director of Modeling, Simulation, and Training, Institute for Creative Technologies, Univ. of Southern California, 12015 E. Waterfront Dr., Los Angeles, CA 90094.

6. Professor and Chair, Sonny Astani Dept. of Civil and Environmental Engineering, Univ. of Southern California, 3620 S. Vermont Ave., Los Angeles, CA 90089. ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Subject

Computer Science Applications,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29CP.1943-5487.0000929

Reference74 articles.

1. Adan A. and D. Huber. 2011. “3D reconstruction of interior wall surfaces under occlusion and clutter.” In Proc. 2011 Int. Conf. on 3D Imaging Modeling Processing Visualization and Transmission 275–281. New York: IEEE.

2. Urban Point Cloud Mining Based on Density Clustering and MapReduce

3. Armeni I. S. Sax A. R. Zamir and S. Savarese. 2017. “Joint 2D-3D-semantic data for indoor scene understanding.” Preprint submitted February 3 2017. https://arxiv.org/abs/1702.01105.

4. Conditional Random Fields Meet Deep Neural Networks for Semantic Segmentation: Combining Probabilistic Graphical Models with Deep Learning for Structured Prediction

5. Classification of sensor independent point cloud data of building objects using random forests;Bassier M.;J. Build. Eng.,2018

Cited by 16 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Deep learning applications for point clouds in the construction industry;Automation in Construction;2024-12

2. A GAN-Augmented CNN Approach for Automated Roadside Safety Assessment of Rural Roadways;Journal of Computing in Civil Engineering;2024-03

3. Automatic Pixel-Level Detection of Structural Steel Elements Using U-Net and Transfer Learning;Computing in Civil Engineering 2023;2024-01-25

4. Unveiling the Road Matrix: Development of Versatile Pavement Surface Models from Low-resolution Aerial Images;2023 IEEE International Conference on Big Data (BigData);2023-12-15

5. Virtual Avatar Representation in the Digital Twin: A Photogrammetric Three-Dimentional Modeling Approach;2023 Eighth International Conference on Informatics and Computing (ICIC);2023-12-08