Euclidean Bundle Adjustment Independent on Camera Intrinsic Parameters

Ezio Malis 1 Adrien Bartoli 2
1 ICARE - Instrumentation, control and architecture of advanced robots
CRISAM - Inria Sophia Antipolis - Méditerranée
2 MOVI - Modeling, localization, recognition and interpretation in computer vision
GRAVIR - IMAG - Graphisme, Vision et Robotique, Inria Grenoble - Rhône-Alpes, CNRS - Centre National de la Recherche Scientifique : FR71
Abstract : This research report presents a bundle adjustment technique which is independe- nt on camera intrinsic parameters. Standard bundle adjustment techniques consider camera intrinsic parameters as unknowns in the optimization process. The scheme proposed in this report differs from previous standard techniques since unknown camera intrinsic parameters are computed as a function of the 3D structure and the camera pose. Considering less unknowns in the optimization process produces a faster algorithm which is more adapted to real-time applications. Computationally expensive metric reconstruction, using for example several zooming cameras, considerably benefits from an intrinsics-free bundle adjustment. Indeed, experimental results, obtained using both simulated data and real images, show that the algorithm we propose not only considerably reduces the computational cost but also improves the accuracy of the metric reconstruction.
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Ezio Malis, Adrien Bartoli. Euclidean Bundle Adjustment Independent on Camera Intrinsic Parameters. RR-4377, INRIA. 2001. ⟨inria-00072211⟩

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