P
Paul Merrell
Researcher at University of North Carolina at Chapel Hill
Publications - 22
Citations - 2615
Paul Merrell is an academic researcher from University of North Carolina at Chapel Hill. The author has contributed to research in topics: Optical flow & Procedural modeling. The author has an hindex of 15, co-authored 21 publications receiving 2421 citations. Previous affiliations of Paul Merrell include Brigham Young University & Stanford University.
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Journal ArticleDOI
Detailed Real-Time Urban 3D Reconstruction from Video
Marc Pollefeys,David Nister,Jan-Michael Frahm,Amir Akbarzadeh,Philippos Mordohai,Brian Clipp,Chris Engels,David Gallup,Seon Joo Kim,Paul Merrell,C. Salmi,Sudipta N. Sinha,B. Talton,Wang Liang,Qingxiong Yang,Henrik Stewenius,Ruigang Yang,Gregory F. Welch,Herman Towles +18 more
TL;DR: A system for automatic, geo-registered, real-time 3D reconstruction from video of urban scenes that extends existing algorithms to meet the robustness and variability necessary to operate out of the lab and shows results on real video sequences comprising hundreds of thousands of frames.
Proceedings ArticleDOI
Real-Time Visibility-Based Fusion of Depth Maps
Paul Merrell,Amir Akbarzadeh,Wang Liang,Philippos Mordohai,Jan-Michael Frahm,Ruigang Yang,David Nister,Marc Pollefeys +7 more
TL;DR: A viewpoint-based approach for the quick fusion of multiple stereo depth maps by selecting depth estimates for each pixel that minimize violations of visibility constraints and thus remove errors and inconsistencies from the depth maps to produce a consistent surface.
Proceedings ArticleDOI
Interactive furniture layout using interior design guidelines
TL;DR: An interactive furniture layout system that assists users by suggesting furniture arrangements that are based on interior design guidelines is presented that measurably increases the quality of furniture arrangements produced by participants with no prior training in interior design.
Proceedings ArticleDOI
Computer-generated residential building layouts
TL;DR: A method for automated generation of building layouts for computer graphics applications using a Bayesian network trained on real-world data to construct a complete three-dimensional building with internal structure.
Proceedings ArticleDOI
Towards Urban 3D Reconstruction from Video
Amir Akbarzadeh,Jan-Michael Frahm,Philippos Mordohai,Brian Clipp,Chris Engels,David Gallup,Paul Merrell,M. Phelps,Sudipta N. Sinha,B. Talton,Wang Liang,Qingxiong Yang,Henrik Stewenius,Ruigang Yang,Gregory F. Welch,Herman Towles,David Nister,Marc Pollefeys +17 more
TL;DR: A data collection system and a processing pipeline for automatic geo-registered 3D reconstruction of urban scenes from video and design processing modules that can achieve fast performance on multiple CPUs and GPUs aiming at real-time performance in the near future are introduced.