A REVIEW OF GEOMETRIC MODELS AND SELF-CALIBRATION METHODS FOR TERRESTRIAL LASER SCANNERS

Terrestrial laser scanning has been shown to be an invaluable technology for engineering measurement applications such as structural deformation measurement and rockfall monitoring. In order to ensure the quality of the data captured for these and other applications, all systematic instrument errors must be properly modelled, calibrated and corrected prior to using the data in subsequent stability or deformation analyses. In one popular modelling approach, the range and angular observations from a laser scanner are augmented with additive model terms that describe the systematic errors. Self-calibration methods can then be used in order to estimate the coefficients of these models. This paper provides a review of the current state-of-the-art of terrestrial laser scanner systematic error models and self-calibration methods, supported by real-dataset examples that demonstrate the need for these processes

Architectural Scene Reconstruction from Single or Multiple Uncalibrated Images

In this paper we present a system for the reconstruction of 3D models of architectural scenes from single or multiple uncalibrated images. The partial 3D model of a building is recovered from a single image using geometric constraints such as parallelism and orthogonality, which are likely to be found in most architectural scenes. The approximate corner positions of a building are selected interactively by a user and then further refined automatically using Hough transform. The relative depths of the corner points are calculated according to the perspective projection model. Partial 3D models recovered from different viewpoints are registered to a common coordinate system for integration. The 3D model registration process is carried out using modified ICP (iterative closest point) algorithm with the initial parameters provided by geometric constraints of the building. The integrated 3D model is then fitted with piecewise planar surfaces to generate a more geometrically consistent model. The acquired images are finally mapped onto the surface of the reconstructed 3D model to create a photo-realistic model. A working system which allows a user to interactively build a 3D model of an architectural scene from single or multiple images has been proposed and implemented

Feasibility of free space quantum key distribution with coherent polarization states

We demonstrate for the first time the feasibility of free space quantum key distribution with continuous variables under real atmospheric conditions. More specifically, we transmit coherent polarization states over a 100m free space channel on the roof of our institute's building. In our scheme, signal and local oscillator are combined in a single spatial mode which auto-compensates atmospheric fluctuations and results in an excellent interference. Furthermore, the local oscillator acts as spatial and spectral filter thus allowing unrestrained daylight operation.Comment: 12 pages, 8 figures, extensions in sections 2, 3.1, 3.2 and 4. This is an author-created, un-copyedited version of an article accepted for publication in New Journal of Physics (Special Issue on Quantum Cryptography: Theory and Practice). IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from i

First Year Wilkinson Microwave Anisotropy Probe (WMAP) Observations: Angular Power Spectrum

We present the angular power spectrum derived from the first-year Wilkinson Microwave Anisotropy Probe (WMAP) sky maps. We study a variety of power spectrum estimation methods and data combinations and demonstrate that the results are robust. The data are modestly contaminated by diffuse Galactic foreground emission, but we show that a simple Galactic template model is sufficient to remove the signal. Point sources produce a modest contamination in the low frequency data. After masking ~700 known bright sources from the maps, we estimate residual sources contribute ~3500 uK^2 at 41 GHz, and ~130 uK^2 at 94 GHz, to the power spectrum l*(l+1)*C_l/(2*pi) at l=1000. Systematic errors are negligible compared to the (modest) level of foreground emission. Our best estimate of the power spectrum is derived from 28 cross-power spectra of statistically independent channels. The final spectrum is essentially independent of the noise properties of an individual radiometer. The resulting spectrum provides a definitive measurement of the CMB power spectrum, with uncertainties limited by cosmic variance, up to l~350. The spectrum clearly exhibits a first acoustic peak at l=220 and a second acoustic peak at l~540 and it provides strong support for adiabatic initial conditions. Kogut et al. (2003) analyze the C_l^TE power spectrum, and present evidence for a relatively high optical depth, and an early period of cosmic reionization. Among other things, this implies that the temperature power spectrum has been suppressed by \~30% on degree angular scales, due to secondary scattering.Comment: One of thirteen companion papers on first-year WMAP results submitted to ApJ; 44 pages, 14 figures; a version with higher quality figures is also available at http://lambda.gsfc.nasa.gov/product/map/map_bibliography.htm

Common and Distinct Components in Data Fusion

In many areas of science multiple sets of data are collected pertaining to the same system. Examples are food products which are characterized by different sets of variables, bio-processes which are on-line sampled with different instruments, or biological systems of which different genomics measurements are obtained. Data fusion is concerned with analyzing such sets of data simultaneously to arrive at a global view of the system under study. One of the upcoming areas of data fusion is exploring whether the data sets have something in common or not. This gives insight into common and distinct variation in each data set, thereby facilitating understanding the relationships between the data sets. Unfortunately, research on methods to distinguish common and distinct components is fragmented, both in terminology as well as in methods: there is no common ground which hampers comparing methods and understanding their relative merits. This paper provides a unifying framework for this subfield of data fusion by using rigorous arguments from linear algebra. The most frequently used methods for distinguishing common and distinct components are explained in this framework and some practical examples are given of these methods in the areas of (medical) biology and food science.Comment: 50 pages, 12 figure

A Self-calibration Algorithm Based on a Unified Framework for Constraints on Multiple Views

In this paper, we propose a new self-calibration algorithm for upgrading projective space to Euclidean space. The proposed method aims to combine the most commonly used metric constraints, including zero skew and unit aspect-ratio by formulating each constraint as a cost function within a unified framework. Additional constraints, e.g., constant principal points, can also be formulated in the same framework. The cost function is very flexible and can be composed of different constraints on different views. The upgrade process is then stated as a minimization problem which may be solved by minimizing an upper bound of the cost function. This proposed method is non-iterative. Experimental results on synthetic data and real data are presented to show the performance of the proposed method and accuracy of the reconstructed scene. © 2012 The Author(s).published_or_final_versionSpringer Open Choice, 25 May 201