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Novel‐View Synthesis of Outdoor Sport Events Using an Adaptive View‐Dependent Geometry
Author(s) -
Germann Marcel,
Popa Tiberiu,
Keiser Richard,
Ziegler Remo,
Gross Markus
Publication year - 2012
Publication title -
computer graphics forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 120
eISSN - 1467-8659
pISSN - 0167-7055
DOI - 10.1111/j.1467-8659.2012.03011.x
Subject(s) - computer science , view synthesis , computer vision , artificial intelligence , point (geometry) , projection (relational algebra) , viewpoints , calibration , computer graphics (images) , geometry , algorithm , rendering (computer graphics) , mathematics , art , statistics , visual arts
We propose a novel fully automatic method for novel‐viewpoint synthesis. Our method robustly handles multi‐camera setups featuring wide‐baselines in an uncontrolled environment. In a first step, robust and sparse point correspondences are found based on an extension of the Daisy features [TLF10]. These correspondences together with back‐projection errors are used to drive a novel adaptive coarse to fine reconstruction method, allowing to approximate detailed geometry while avoiding an extreme triangle count. To render the scene from arbitrary viewpoints we use a view‐dependent blending of color information in combination with a view‐dependent geometry morph. The view‐dependent geometry compensates for misalignments caused by calibration errors. We demonstrate that our method works well under arbitrary lighting conditions with as little as two cameras featuring wide‐baselines. The footage taken from real sports broadcast events contains fine geometric structures, which result in nice novel‐viewpoint renderings despite of the low resolution in the images.