6 research outputs found
Aerial video geo-registration using terrain models from dense and coherent stereo matching
In the context of aerial imagery, one of the first steps toward a coherent processing of the information contained
in multiple images is geo-registration, which consists in assigning geographic 3D coordinates to the pixels of the
image. This enables accurate alignment and geo-positioning of multiple images, detection of moving objects
and fusion of data acquired from multiple sensors.
To solve this problem there are different approaches that
require, in addition to a precise characterization of the camera sensor, high resolution referenced images or terrain
elevation models, which are usually not publicly available or out of date. Building upon the idea of developing
technology that does not need a reference terrain elevation model, we propose a geo-registration technique that
applies variational methods to obtain a dense and coherent surface elevation model that is used to replace the
reference model. The surface elevation model is built by interpolation of scattered 3D points, which are obtained
in a two-step process following a classical stereo pipeline: first, coherent disparity maps between image pairs
of a video sequence are estimated and then image point correspondences are back-projected.
The proposed variational method enforces continuity of the disparity map not only along epipolar lines (as done by previous geo-registration techniques) but also across them, in the full 2D image domain. In the experiments, aerial images from synthetic video sequences have been used to validate the proposed technique
QUARCH: A New Quasi-Affine Reconstruction Stratum From Vague Relative Camera Orientation Knowledge
International audienceWe present a new quasi-affine reconstruction of a scene and its application to camera self-calibration. We refer to this reconstruction as QUARCH (QUasi-Affine Reconstruction with respect to Camera centers and the Hodographs of horopters). A QUARCH can be obtained by solving a semidefinite programming problem when, (i) the images have been captured by a moving camera with constant intrinsic parameters, and (ii) a vague knowledge of the relative orientation (under or over 120°) between camera pairs is available. The resulting reconstruction comes close enough to an affine one allowing thus an easy upgrade of the QUARCH to its affine and metric counterparts. We also present a constrained Levenberg-Marquardt method for nonlinear optimization subject to Linear Matrix Inequality (LMI) constraints so as to ensure that the QUARCH LMIs are satisfied during optimization. Experiments with synthetic and real data show the benefits of QUARCH in reliably obtaining a metric reconstruction
QUARCH: A New Quasi-Affine Reconstruction Stratum From Vague Relative Camera Orientation Knowledge
International audienceWe present a new quasi-affine reconstruction of a scene and its application to camera self-calibration. We refer to this reconstruction as QUARCH (QUasi-Affine Reconstruction with respect to Camera centers and the Hodographs of horopters). A QUARCH can be obtained by solving a semidefinite programming problem when, (i) the images have been captured by a moving camera with constant intrinsic parameters, and (ii) a vague knowledge of the relative orientation (under or over 120°) between camera pairs is available. The resulting reconstruction comes close enough to an affine one allowing thus an easy upgrade of the QUARCH to its affine and metric counterparts. We also present a constrained Levenberg-Marquardt method for nonlinear optimization subject to Linear Matrix Inequality (LMI) constraints so as to ensure that the QUARCH LMIs are satisfied during optimization. Experiments with synthetic and real data show the benefits of QUARCH in reliably obtaining a metric reconstruction
Camera Autocalibration and Horopter Curves
We describe a new algorithm for the obtainment of the affine and Euclidean calibration of a camera
under general motion. The algorithm exploit the relationships of the horopter curves associated to each pair of
cameras with the plane at infinity and the absolute conic. Using these properties we define cost functions whose
minimization by means of general purpose techniques provides the required calibration. The experiments show the
good convergence properties, computational efficiency and robust performance of the new techniques