Dr. Muhammad Zeshan Afzal

Prof. Dr. Didier Stricker

Dr. Alain Pagani

Keonna Cunningham

Dr. Oliver Wasenmüller

Dr. Gabriele Bleser

Dr. Bruno Mirbach

Dr. Jason Raphael Rambach

Dr. Bertram Taetz

Mhd Rashed Al Koutayni

Jilliam Maria Diaz Barros

Iuliia Brishtel

Mahdi Chamseddine

Steve Dias da Cruz

Ahmet Firintepe

Sophie Folawiyo

David Michael Fürst

Kamalveerkaur Garewal

Christiano Couto Gava

Leif Eric Goebel

Tewodros Amberbir Habtegebrial

Jigyasa Singh Katrolia

Andreas Kölsch

Onorina Kovalenko

Muhammad Jameel Nawaz Malik

Nareg Minaskan Karabid

Mohammad Minouei

Manthan Pancholi

Engr. Kumail Raza

Dr. Nadia Robertini

María Alejandra Sánchez Marín

Dr. Kripasindhu Sarkar

Alexander Schäfer

Pascal Schneider

Lukas Stefan Staecker

Dr. Vladislav Golyanik

Dr. Aditya Tewari

André Luiz Brandão

SPHERA – A Unifying Structure from Motion Framework for Central Projection Cameras

SPHERA – A Unifying Structure from Motion Framework for Central Projection Cameras
Christiano Couto Gava, Didier Stricker
International Conference on Computer Vision Theory and Applications (VISAPP-15), 10th, March 11-14, Berlin, Germany

Abstract:: As multi-view reconstruction techniques evolve, they accomplish to reconstruct larger environments. This is possible due to the availability of vast image collections of the target scenes. Within the next years it will be necessary to account for all available sources of visual information to supply future 3D reconstruction approaches. Accordingly, Structure from Motion (SfM) algorithms will need to handle such variety of image sources, i.e. perspective, wide-angle or spherical images. Although SfM for perspective and spherical images as well as catadioptric systems have already been studied, state of the art algorithms are not able to deal with these images simultaneously. To close this gap, we developed SPHERA, a unifying SfM framework designed for central projection cameras. It uses a sphere as underlying model, allowing single effective viewpoint vision systems to be treated in a unified way. We validate our framework with quantitative evaluations on synthetic spherical as well as real perspective, spherical and hybrid image datasets. Results show that SPHERA is a powerful framework to support upcoming algorithms and applications on large scale 3D reconstruction.

Keywords:: Spherical Images, Structure from Motion, Central Projection Cameras, 3D Reconstruction

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