A Newton method for pose refinement of 3D models

Different optimization methods can be employed to optimize a numerical estimate for the match between an instantiated object model and an image. In order to take advantage of gradient-based optimization methods, perspective inversion must be used in this context. We show that convergence can be very fast by extrapolating to maximum goodness-of-fit with Newton's method. This approach is related to methods which either maximize a similar goodness-of-fit measure without use of gradient information, or else minimize distances between projected model lines and image features. Newton's method combines the accuracy of the former approach with the speed of convergence of the latter.

Approximate Gauss-Newton methods for nonlinear least squares problems

The Gauss–Newton algorithm is an iterative method regularly used for solving nonlinear least squares problems. It is particularly well suited to the treatment of very large scale variational data assimilation problems that arise in atmosphere and ocean forecasting. The procedure consists of a sequence of linear least squares approximations to the nonlinear problem, each of which is solved by an “inner” direct or iterative process. In comparison with Newton’s method and its variants, the algorithm is attractive because it does not require the evaluation of second-order derivatives in the Hessian of the objective function. In practice the exact Gauss–Newton method is too expensive to apply operationally in meteorological forecasting, and various approximations are made in order to reduce computational costs and to solve the problems in real time. Here we investigate the effects on the convergence of the Gauss–Newton method of two types of approximation used commonly in data assimilation. First, we examine “truncated” Gauss–Newton methods where the inner linear least squares problem is not solved exactly, and second, we examine “perturbed” Gauss–Newton methods where the true linearized inner problem is approximated by a simplified, or perturbed, linear least squares problem. We give conditions ensuring that the truncated and perturbed Gauss–Newton methods converge and also derive rates of convergence for the iterations. The results are illustrated by a simple numerical example. A practical application to the problem of data assimilation in a typical meteorological system is presented.

Politics and the Paul's Cross sermons, 1558-1642

A study of England's most important pulpit of the Reformation period with a detailed discussion of the rhetorical and interpretative strategies used by preachers on politically sensitive subjects and occasions.

A survey for planetary transits in the field of NGC 7789

We present results from 30 nights of observations of the open cluster NGC 7789 with the Wide Field Camera on the Isaac Newton Telescope, La Palma. From ~900 epochs, we obtained light curves and Sloan r'-i' colours for ~33000 stars, with ~2400 stars having better than 1 per cent precision. We expected to detect ~2 transiting hot Jupiter planets if 1 per cent of stars host such a companion and a typical hot Jupiter radius is ~1.2R_J. We find 24 transit candidates, 14 of which we can assign a period. We rule out the transiting planet model for 21 of these candidates using various robust arguments. For two candidates, we are unable to decide on their nature, although it seems most likely that they are eclipsing binaries as well. We have one candidate exhibiting a single eclipse, for which we derive a radius of 1.81+0.09-0.00R_J. Three candidates remain that require follow-up observations in order to determine their nature.