Dr. Muhammad Zeshan Afzal
Prof. Dr. Didier Stricker
Dr. Alain Pagani
Dr. Gerd Reis
Eric Thil
Keonna Cunningham
Dr. Oliver Wasenmüller
Dr. Gabriele Bleser
Dr. Bruno Mirbach
Dr. Jason Raphael Rambach
Dr. Bertram Taetz
Sk Aziz Ali
Mhd Rashed Al Koutayni
Murad Almadani
Alaa Alshubbak
Yuriy Anisimov
Jilliam Maria Diaz Barros
Ramy Battrawy
Iuliia Brishtel
Hammad Butt
Mahdi Chamseddine
Steve Dias da Cruz
Fangwen Shu
Torben Fetzer
Ahmet Firintepe
Sophie Folawiyo
David Michael Fürst
Kamalveerkaur Garewal
Christiano Couto Gava
Leif Eric Goebel
Tewodros Amberbir Habtegebrial
Simon Häring
Khurram Hashmi
Jigyasa Singh Katrolia
Andreas Kölsch
Onorina Kovalenko
Stephan Krauß
Paul Lesur
Muhammad Jameel Nawaz Malik
Michael Lorenz
Markus Miezal
Mina Ameli
Nareg Minaskan Karabid
Mohammad Minouei
Pramod Murthy
Mathias Musahl
Peter Neigel
Manthan Pancholi
Qinzhuan Qian
Engr. Kumail Raza
Dr. Nadia Robertini
María Alejandra Sánchez Marín
Dr. Kripasindhu Sarkar
Alexander Schäfer
Pascal Schneider
René Schuster
Mohamed Selim
Lukas Stefan Staecker
Dennis Stumpf
Yongzhi Su
Xiaoying Tan
Yaxu Xie
Dr. Vladislav Golyanik
Dr. Aditya Tewari
André Luiz Brandão
A Generalized Structure from Motion Framework for Central Projection Cameras
A Generalized Structure from Motion Framework for Central Projection Cameras
International Joint Conference on Computer Vision, Imaging and Computer Graphics (VISIGRAPP-2015), 10th, March 11-14, Berlin, Germany
- Abstract:
- This paper presents a novel Structure from Motion (SfM) framework designed for central projection cameras. The goal is to support future large scale multi-view 3D reconstruction algorithms. We believe that these algorithms will be able to benefit from several different sources of visual information. Accordingly, SfM approaches will need to handle this variety of image sources, such as perspective, wide-angle and spherical images. However, this issue has not yet been addressed. Current state of the art techniques are not able to handle heterogeneous images simultaneously. Therefore, we introduce SPHERA, a generalized SfM framework designed for central projection cameras. By adopting the unit sphere as underlying model it is possible to treat single effective viewpoint cameras in a unified way. We validate our framework on synthetic and real datasets. Results show that SPHERA is a powerful framework to support upcoming algorithms and applications on large scale 3D reconstruction.
- Keywords:
- Structure from motion, spherical images, multi-view 3D reconstruction, large scale