Cavlectometry: Towards Holistic Reconstruction of Large Mirror Objects

We introduce a method based on the deflectometry principle for the reconstruction of specular objects exhibiting significant size and geometric complexity. A key feature of our approach is the deployment of an Automatic Virtual Environment (CAVE) as pattern generator. To unfold the full power of this extraordinary experimental setup, an optical encoding scheme is developed which accounts for the distinctive topology of the CAVE. Furthermore, we devise an algorithm for detecting the object of interest in raw deflectometric images. The segmented foreground is used for single-view reconstruction, the background for estimation of the camera pose, necessary for calibrating the sensor system. Experiments suggest a significant gain of coverage in single measurements compared to previous methods. To facilitate research on specular surface reconstruction, we will make our data set publicly available

The Footprint Database and Web Services of the Herschel Space Observatory

Data from the Herschel Space Observatory is freely available to the public but no uniformly processed catalogue of the observations has been published so far. To date, the Herschel Science Archive does not contain the exact sky coverage (footprint) of individual observations and supports search for measurements based on bounding circles only. Drawing on previous experience in implementing footprint databases, we built the Herschel Footprint Database and Web Services for the Herschel Space Observatory to provide efficient search capabilities for typical astronomical queries. The database was designed with the following main goals in mind: (a) provide a unified data model for meta-data of all instruments and observational modes, (b) quickly find observations covering a selected object and its neighbourhood, (c) quickly find every observation in a larger area of the sky, (d) allow for finding solar system objects crossing observation fields. As a first step, we developed a unified data model of observations of all three Herschel instruments for all pointing and instrument modes. Then, using telescope pointing information and observational meta-data, we compiled a database of footprints. As opposed to methods using pixellation of the sphere, we represent sky coverage in an exact geometric form allowing for precise area calculations. For easier handling of Herschel observation footprints with rather complex shapes, two algorithms were implemented to reduce the outline. Furthermore, a new visualisation tool to plot footprints with various spherical projections was developed. Indexing of the footprints using Hierarchical Triangular Mesh makes it possible to quickly find observations based on sky coverage, time and meta-data. The database is accessible via a web site (http://herschel.vo.elte.hu) and also as a set of REST web service functions.Comment: Accepted for publication in Experimental Astronom

Real-Time Mapping Using Stereoscopic Vision Optimization

This research focuses on efficient methods of generating 2D maps from stereo vision in real-time. Instead of attempting to locate edges between objects, we make the assumption that the representative surfaces of objects in a view provide enough information to generate a map while taking less time to locate during processing. Since all real-time vision processing endeavors are extremely computationally intensive, numerous optimization techniques are applied to allow for a real-time application: horizontal spike smoothing for post-disparity noise, masks to focus on close-proximity objects, melding for object synthesis, and rectangular fitting for object extraction under a planar assumption. Additionally, traditional image transformation mechanisms such as rotation, translation, and scaling are integrated. Results from our research are an encouraging 10Hz with no vision post processing and accuracy up to 11 feet. Finally, vision mapping results are compared to simultaneously collected sonar data in three unique experimental settings

Computer vision

The field of computer vision is surveyed and assessed, key research issues are identified, and possibilities for a future vision system are discussed. The problems of descriptions of two and three dimensional worlds are discussed. The representation of such features as texture, edges, curves, and corners are detailed. Recognition methods are described in which cross correlation coefficients are maximized or numerical values for a set of features are measured. Object tracking is discussed in terms of the robust matching algorithms that must be devised. Stereo vision, camera control and calibration, and the hardware and systems architecture are discussed

Trapped-modes, slow light and collective resonances in metamaterials

A new class of metamaterials exhibiting coherent, collective response has been introduced. It is shown that the sharp resonant behaviour of coherent metamaterials can only be observed in arrays of metamaterial elements and is absent from the response of a single isolated unit cell. As a result, such arrays are extremely sensitive to positional disorder and resonances degrade rapidly with increasing randomization. These observed strong inter-element interactions render coherent metamaterials ideal candidates for gain-assisted functionalities as demonstrated by the suggestion and numerical study of a novel amplifying/lasing device, termed the 'lasing spaser'. An antipode class of incoherent metamaterials is also presented, where the resonant response of a single unit and of an infinite array are very similar resulting in weak dependence on disorder. The first metamaterial analogue of electromagnetically induced transparency is demonstrated experimentally and theoretically in essentially planar structures. The phenomenon arises from destructive interference of fields radiated by strongly coupled metamaterial elements that support anti-symmetric weakly-radiating current configurations, termed trapped-modes. This behaviour is accompanied by sharp resonances and steep normal dispersion which leads to long pulse delays. It is shown that cascading of metamaterial slabs increases the bandwidth of the pulse delay effect, while extension to all-angles and all-polarizations is demonstrated by appealing to incoherent metamaterials. The first experimental study of metamaterials with toroidal symmetry is reported. Resonant circular dichroism is observed in a metamaterial consisting of toroidal wire windings. Further numerical investigation attributes the gyrotropic behaviour to current standing waves corresponding to the eigenmodes of the unit cell winding. Multipole expansion of the resonant current configurations indicates a dominant electric dipole-magnetic dipole contribution to gyrotropy followed by electric dipole-electric quadrupole order effects, while a non-negligible toroidal response comparable to electric quadrupole in scattering efficiency also emerges. Finally, collective effects are studied in quasicrystal hole arrays and it is demonstrated that non-resonant scatterers can lead to strong lattice resonances and extraordinary transmission even in the case of quasi-periodicity. Microwave and optical quasicrystal patterns exhibit similar response exceeding predictions based on absence of inter-element interactions and even reaching a nearly invisible state in the microwave part of the spectrum

Optimal source localization and tracking using arrays with uncertainties in sensor locations

We develop a computationally efficient iterative algorithm for source localization and tracking using active/passive arrays with uncertainties in sensor locations. We suppose that the available data consist of time delay, or differential time delay, measurements of the signal wavefront across the array. We consider a general senario in which the array uncertainties may be correlated in time and in space. The proposed algorithm is optimal in the sense that it converges montonically to the Maximum Likelihood (ML) estimate of the source trajectory parameters. In the case of multiple sources, the algorithm makes an essential use of the information available from all sources to reduce the array uncertainties (the so-called array callibration) and thus to improve the localization accuracy of each signal source. We also derive new expressions for the log-likelihood gradient, the Hessian, and the Fisher's information matrix, that may be used for efficient implementation of gradient based algorithms, and for assessing the mean square error of the resulting ML parameter estimates.Funding was provided by the Office of Naval Research under contract Number N00014-85-K-0272

Semi-Automated DIRSIG scene modeling from 3D lidar and passive imagery

The Digital Imaging and Remote Sensing Image Generation (DIRSIG) model is an established, first-principles based scene simulation tool that produces synthetic multispectral and hyperspectral images from the visible to long wave infrared (0.4 to 20 microns). Over the last few years, significant enhancements such as spectral polarimetric and active Light Detection and Ranging (lidar) models have also been incorporated into the software, providing an extremely powerful tool for multi-sensor algorithm testing and sensor evaluation. However, the extensive time required to create large-scale scenes has limited DIRSIG’s ability to generate scenes ”on demand.” To date, scene generation has been a laborious, time-intensive process, as the terrain model, CAD objects and background maps have to be created and attributed manually. To shorten the time required for this process, this research developed an approach to reduce the man-in-the-loop requirements for several aspects of synthetic scene construction. Through a fusion of 3D lidar data with passive imagery, we were able to semi-automate several of the required tasks in the DIRSIG scene creation process. Additionally, many of the remaining tasks realized a shortened implementation time through this application of multi-modal imagery. Lidar data is exploited to identify ground and object features as well as to define initial tree location and building parameter estimates. These estimates are then refined by analyzing high-resolution frame array imagery using the concepts of projective geometry in lieu of the more common Euclidean approach found in most traditional photogrammetric references. Spectral imagery is also used to assign material characteristics to the modeled geometric objects. This is achieved through a modified atmospheric compensation applied to raw hyperspectral imagery. These techniques have been successfully applied to imagery collected over the RIT campus and the greater Rochester area. The data used include multiple-return point information provided by an Optech lidar linescanning sensor, multispectral frame array imagery from the Wildfire Airborne Sensor Program (WASP) and WASP-lite sensors, and hyperspectral data from the Modular Imaging Spectrometer Instrument (MISI) and the COMPact Airborne Spectral Sensor (COMPASS). Information from these image sources was fused and processed using the semi-automated approach to provide the DIRSIG input files used to define a synthetic scene. When compared to the standard manual process for creating these files, we achieved approximately a tenfold increase in speed, as well as a significant increase in geometric accuracy