Real-Time Shape Acquisition with Sensor-Specific Precision | TU Wien

The core idea in this project is to capture the shape of physical objects in real time, with guaranteed precision, and to reconstruct the shape boundaries with minimal geometry. An example application is to let untrained users acquire shapes using emerging mobile sensing devices such as Google’s Project Tango. The user moves the sensor around the object, guided by immediate visual feedback on the input sampling quality. The output is a topologically clean mesh consisting of just the vertices required to represent its features to the desired approximation. The real-time reconstruction enables numerous geometry-processing applications to be taken online, such as shape retrieval/matching, harvesting real-world geometry into a cloud, perspective photo correction, interactive modeling, augmented reality, physics simulation, or fabrication.

Funding

FWF P24600-N23

Team

Stefan Ohrhallinger

Research Areas

Geometry Processing
Uses concepts from applied mathematics and computer science to design efficient algorithms for the reconstruction, analysis, manipulation, simulation and transmission of complex 3D models. Example applications are collision detection, reconstruction, compression, occlusion-aware surface handling and improved sampling conditions.

Publications

12 Publications found:

Image	Bib Reference	Publication Type
2021
	Mohamed Radwan, Stefan Ohrhallinger, Michael Wimmer Fast occlusion-based point cloud exploration The Visual Computer Journal, 37:2769-2781, September 2021. [paper]	Journal Paper with Conference Talk
2020
	Philipp Erler , Paul Guerrero, Stefan Ohrhallinger, Michael Wimmer , Niloy Mitra Points2Surf: Learning Implicit Surfaces from Point Clouds In Computer Vision -- ECCV 2020, pages 108-124. October 2020. [points2surf_paper] [short video]	Conference Paper
2019
	Horst Gruber Extensible Image Classification	Bachelor Thesis
	Stefan Ohrhallinger, Michael Wimmer FitConnect: Connecting Noisy 2D Samples by Fitted Neighborhoods Computer Graphics Forum, 38(1):126-137, February 2019. [paper] [Replicability Source Code]	Journal Paper with Conference Talk
2018
	Stefan Ohrhallinger, Michael Wimmer StretchDenoise: Parametric Curve Reconstruction with Guarantees by Separating Connectivity from Residual Uncertainty of Samples In Proceedings of Pacific Graphics 2018, pages 1-4. August 2018. [image] [paper] [Extended version] [source]	Conference Paper
2017
	Michael Pointner Multi-Focal Image Generation using Automatic Depth-Based Focus Selection [image] [thesis]	Bachelor Thesis
	Nicolas Grossmann Extracting Sensor Specific Noise Models [thesis]	Bachelor Thesis
	Thomas Köppel Extracting Noise Models – considering X / Y and Z Noise [thesis]	Bachelor Thesis
	Mohamed Radwan, Stefan Ohrhallinger, Elmar Eisemann, Michael Wimmer Cut and Paint: Occlusion-Aware Subset Selection for Surface Processing In Proceedings of Graphics Interface 2017, pages 82-89. May 2017. [paper]	Conference Paper
	Siegfried Reinwald Fast kNN in Screen Space on GPU [image] [thesis]	Bachelor Thesis
2016
	Jeremy Forsythe, Vitaliy Kurlin, Andrew Fitzgibbon Resolution-independent superpixels based on convex constrained meshes without small angles Lecture Notes in Computer Science (LNCS), 10072:223-233, December 2016. [paper] [slides]	Journal Paper with Conference Talk
	Stefan Ohrhallinger, Scott A. Mitchell, Michael Wimmer Curve Reconstruction with Many Fewer Samples Computer Graphics Forum, 35(5):167-176, 2016. [paper] [slides] [Reproducibility Source Code]	Journal Paper with Conference Talk