Computer Science – Computer Vision and Pattern Recognition
Scientific paper
2006-10-11
Journal of Mathematical Imaging and Vision 32, 1 (2008) 73-87
Computer Science
Computer Vision and Pattern Recognition
21 pages, version modifi\'ee accept\'e le 20 mars 2008
Scientific paper
10.1007/s10851-008-0086-1
In this paper, we propose a global method for estimating the motion of a camera which films a static scene. Our approach is direct, fast and robust, and deals with adjacent frames of a sequence. It is based on a quadratic approximation of the deformation between two images, in the case of a scene with constant depth in the camera coordinate system. This condition is very restrictive but we show that provided translation and depth inverse variations are small enough, the error on optical flow involved by the approximation of depths by a constant is small. In this context, we propose a new model of camera motion, that allows to separate the image deformation in a similarity and a ``purely'' projective application, due to change of optical axis direction. This model leads to a quadratic approximation of image deformation that we estimate with an M-estimator; we can immediatly deduce camera motion parameters.
Dibos Françoise
Jonchery Claire
Koepfler Georges
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