Authors:
Christiano Couto Gava
and
Didier Stricker
Affiliation:
German Research Center for Artificial Intelligence and Technical University of Kaiserslautern, Germany
Keyword(s):
Spherical Images, Structure from Motion, Central Projection Cameras, 3D Reconstruction
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Applications and Services
;
Computer Vision, Visualization and Computer Graphics
;
Entertainment Imaging Applications
;
Geometry and Modeling
;
Image-Based Modeling
;
Imaging for Cultural Heritage (Modeling/Simulation, Virtual Restoration)
;
Motion, Tracking and Stereo Vision
;
Pattern Recognition
;
Software Engineering
;
Stereo Vision and Structure from Motion
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 a
s 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.
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