Kinect Range Sensing: Structured-Light versus Time-of-Flight Kinect

Recently, the new Kinect One has been issued by Microsoft, providing the next generation of real-time range sensing devices based on the Time-of-Flight (ToF) principle. As the first Kinect version was using a structured light approach, one would expect various differences in the characteristics of the range data delivered by both devices. This paper presents a detailed and in-depth comparison between both devices. In order to conduct the comparison, we propose a framework of seven different experimental setups, which is a generic basis for evaluating range cameras such as Kinect. The experiments have been designed with the goal to capture individual effects of the Kinect devices as isolatedly as possible and in a way, that they can also be adopted, in order to apply them to any other range sensing device. The overall goal of this paper is to provide a solid insight into the pros and cons of either device. Thus, scientists that are interested in using Kinect range sensing cameras in their specific application scenario can directly assess the expected, specific benefits and potential problem of either device.Comment: 58 pages, 23 figures. Accepted for publication in Computer Vision and Image Understanding (CVIU

Experimental investigation of some aspects of insect-like flapping flight aerodynamics for application to micro air vehicles

Insect-like flapping flight offers a power-efficient and highly manoeuvrable basis for micro air vehicles for indoor applications. Some aspects of the aerodynamics associated with the sweeping phase of insect wing kinematics are examined by making particle image velocimetry measurements on a rotating wing immersed in a tank of seeded water. The work is motivated by the paucity of data with quantified error on insect-like flapping flight, and aims to fill this gap by providing a detailed description of the experimental setup, quantifying the uncertainties in the measurements and explaining the results. The experiments are carried out at two Reynolds numbers-500 and 15,000-accounting for scales pertaining to many insects and future flapping-wing micro air vehicles, respectively. The results from the experiments are used to describe prominent flow features, and Reynolds number-related differences are highlighted. In particular, the behaviour of the leading-edge vortex at these Reynolds numbers is studied and the presence of Kelvin-Helmholtz instability observed at the higher Reynolds number in computational fluid dynamics calculations is also verified

Depth from Monocular Images using a Semi-Parallel Deep Neural Network (SPDNN) Hybrid Architecture

Deep neural networks are applied to a wide range of problems in recent years. In this work, Convolutional Neural Network (CNN) is applied to the problem of determining the depth from a single camera image (monocular depth). Eight different networks are designed to perform depth estimation, each of them suitable for a feature level. Networks with different pooling sizes determine different feature levels. After designing a set of networks, these models may be combined into a single network topology using graph optimization techniques. This "Semi Parallel Deep Neural Network (SPDNN)" eliminates duplicated common network layers, and can be further optimized by retraining to achieve an improved model compared to the individual topologies. In this study, four SPDNN models are trained and have been evaluated at 2 stages on the KITTI dataset. The ground truth images in the first part of the experiment are provided by the benchmark, and for the second part, the ground truth images are the depth map results from applying a state-of-the-art stereo matching method. The results of this evaluation demonstrate that using post-processing techniques to refine the target of the network increases the accuracy of depth estimation on individual mono images. The second evaluation shows that using segmentation data alongside the original data as the input can improve the depth estimation results to a point where performance is comparable with stereo depth estimation. The computational time is also discussed in this study.Comment: 44 pages, 25 figure

Large scale EPR correlations and cosmic gravitational waves

We study how quantum correlations survive at large scales in spite of their exposition to stochastic backgrounds of gravitational waves. We consider Einstein-Podolski-Rosen (EPR) correlations built up on the polarizations of photon pairs and evaluate how they are affected by the cosmic gravitational wave background (CGWB). We evaluate the quantum decoherence of the EPR correlations in terms of a reduction of the violation of the Bell inequality as written by Clauser, Horne, Shimony and Holt (CHSH). We show that this decoherence remains small and that EPR correlations can in principle survive up to the largest cosmic scales.Comment: 5 figure

Metamodelling of multivariable engine models for real-time flight simulation.

Sophisticated real-time distributed flight simulation environments may be constructed from a wide range of modelling and simulation tools. In this way accuracy, detail and model flexibility may be incorporated into the simulator. Distributed components may be constructed by a wide range of methods, from high level environments such as Matlab, through coded environments such as C or Fortran to hardware-in-the- loop. In this paper the Response Surface Methodology is combined with a hyper-heuristic (evolutionary algorithm) and applied to the representation of computationally intensive non-linear multivariable engine modelling. The paper investigates the potential for metamodelling (models of models) dynamic models which were previously too slow to be included in multi-component, high resolution real-time simulation environments. A multi-dimensional gas turbine model with five primary control inputs, six environmental inputs and eleven outputs is considered. An investigation has been conducted to ascertain to what extent these systems can be approximated by response surfaces with experiments which have been designed by hyper-heuristics as a first step towards automatic modelling methodology

Advanced space information systems

Onboard computers for pre-transmission data processing, automation of data acquisition centers, and real time data relay to control centers for advanced space information system

Nab: Measurement Principles, Apparatus and Uncertainties

The Nab collaboration will perform a precise measurement of 'a', the electron-neutrino correlation parameter, and 'b', the Fierz interference term in neutron beta decay, in the Fundamental Neutron Physics Beamline at the SNS, using a novel electric/magnetic field spectrometer and detector design. The experiment is aiming at the 10^{-3} accuracy level in (Delta a)/a, and will provide an independent measurement of lambda = G_A/G_V, the ratio of axial-vector to vector coupling constants of the nucleon. Nab also plans to perform the first ever measurement of 'b' in neutron decay, which will provide an independent limit on the tensor weak coupling.Comment: 12 pages, 6 figures, 1 table, talk presented at the International Workshop on Particle Physics with Slow Neutrons, Grenoble, 29-31 May 2008; to appear in Nucl. Instrum. Meth. in Physics Research

A preliminary experiment definition for video landmark acquisition and tracking

Six scientific objectives/experiments were derived which consisted of agriculture/forestry/range resources, land use, geology/mineral resources, water resources, marine resources and environmental surveys. Computer calculations were then made of the spectral radiance signature of each of 25 candidate targets as seen by a satellite sensor system. An imaging system capable of recognizing, acquiring and tracking specific generic type surface features was defined. A preliminary experiment definition and design of a video Landmark Acquisition and Tracking system is given. This device will search a 10-mile swath while orbiting the earth, looking for land/water interfaces such as coastlines and rivers