Search
Publication Authors

Prof. Dr. Didier Stricker

Dr. Alain Pagani

Dr. Gerd Reis

Eric Thil

Keonna Cunningham

Dr. Oliver Wasenmüller

Dr. Muhammad Zeshan Afzal

Dr. Gabriele Bleser

Dr. Muhammad Jameel Nawaz Malik
Dr. Bruno Mirbach

Dr. Jason Raphael Rambach

Dr. Nadia Robertini

Dr. René Schuster

Dr. Bertram Taetz

Ahmed Aboukhadra

Sk Aziz Ali

Mhd Rashed Al Koutayni

Yuriy Anisimov

Jilliam Maria Diaz Barros

Ramy Battrawy
Hammad Butt

Mahdi Chamseddine

Steve Dias da Cruz
Fangwen Shu

Torben Fetzer

Ahmet Firintepe
Sophie Folawiyo

David Michael Fürst

Christiano Couto Gava

Tewodros Amberbir Habtegebrial
Simon Häring

Khurram Azeem Hashmi
Henri Hoyez

Jigyasa Singh Katrolia

Andreas Kölsch
Onorina Kovalenko

Stephan Krauß
Paul Lesur

Michael Lorenz

Dr. Markus Miezal

Mina Ameli

Nareg Minaskan Karabid

Mohammad Minouei

Pramod Murthy

Mathias Musahl

Peter Neigel

Manthan Pancholi
Mariia Podguzova

Praveen Nathan
Qinzhuan Qian
Rishav
Marcel Rogge
María Alejandra Sánchez Marín
Dr. Kripasindhu Sarkar

Alexander Schäfer

Pascal Schneider

Mohamed Selim

Tahira Shehzadi
Lukas Stefan Staecker

Yongzhi Su

Xiaoying Tan
Christian Witte

Yaxu Xie

Vemburaj Yadav

Dr. Vladislav Golyanik

Dr. Aditya Tewari

André Luiz Brandão
Publication Archive
New title
- ActivityPlus
- AlterEgo
- AR-Handbook
- ARVIDA
- Auroras
- AVILUSplus
- Be-greifen
- Body Analyzer
- CAPTURE
- COGNITO
- DAKARA
- Density
- DYNAMICS
- EASY-IMP
- Eyes Of Things
- iACT
- IMCVO
- IVMT
- LARA
- LiSA
- Marmorbild
- Micro-Dress
- Odysseus Studio
- On Eye
- OrcaM
- PAMAP
- PROWILAN
- ServiceFactory
- STREET3D
- SUDPLAN
- SwarmTrack
- TuBUs-Pro
- VIDETE
- VIDP
- VisIMon
- VISTRA
- You in 3D
Correspondence Chaining for Enhanced Dense 3D Reconstruction
Correspondence Chaining for Enhanced Dense 3D Reconstruction
Oliver Wasenmüller, Bernd Krolla, Francesco Michielin, Didier Stricker
Communication Papers Proceedings of the International Conference on Computer Graphics, Visualization and Computer Vision (WSCG) International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision (WSCG-22)
- Abstract:
- Within the computer vision community, the reconstruction of rigid 3D objects is a well known task in current research. Many existing algorithms provide a dense 3D reconstruction of a rigid object from sequences of 2D images. Commonly, an iterative registration approach is applied for these images, relying on pairwise dense matches between images, which are then triangulated. To minimize redundant and imprecisely reconstructed 3D points, we present and evaluate a new approach, called Correspondence Chaining, to fuse existing dense twoview 3D reconstruction algorithms to a multi-view reconstruction, where each 3D point is estimated from multiple images. This leads to an enhanced precision and reduced redundancy. The algorithm is evaluated with three different representative datasets. With Correspondence Chaining the mean error of the reconstructed pointclouds related to ground truth data, acquired with a laser scanner, can be reduced by up to 40%, whereas the root mean square error is even reduced by up to 56%. The reconstructed 3D models contain much less 3D points, while keeping details like fine structures, the file size is reduced by up to 78% and the computation time of the involved parts is decreased by up to 42%.
- Keywords:
- computer vision, dense 3D reconstruction, perspective SfM, multi view reconstruction