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Global Optimization of Object Pose and Motion from a Single Rolling Shutter Image with Automatic 2D-3D Matching
Ludovic Magerand1, 2, Adrien Bartoli2, Omar Ait-Aider1, and Daniel Pizarro3
1Institut Pascal, Université Blaise Pascal, Clermont-Ferrand, France
2ISIT, Université d’Auvergne, Clermont-Ferrand, France
3University of Alcala, Alcala de Henares, Spain
Abstract. Low cost CMOS cameras can have an acquisition mode called rolling shutter which sequentially exposes the scan-lines. When a single object moves with respect to the camera, this creates image distortions. Assuming 2D-3D correspondences known, previous work showed that the object pose and kinematics can be estimated from a single rolling shutter image. This was achieved using a suboptimal initialization followed by local iterative optimization.
We propose a polynomial projection model for rolling shutter cameras and a constrained global optimization of its parameters. This is done by means of a semidefinite programming problem obtained from the generalized problem of moments method. Contrarily to previous work, our optimization does not require an initialization and ensures that the global minimum is achieved. This allows us to build automatically robust 2D-3D correspondences using a template to provide an initial set of correspondences.
Experiments show that our method slightly improves previous work on both simulated and real data. This is due to local minima into which previous methods get trapped. We also successfully experimented building 2D-3D correspondences automatically with both simulated and real data.
Keywords: rolling shutter, motion estimation, matching
LNCS 7572, p. 456 ff.
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© Springer-Verlag Berlin Heidelberg 2012