Experimental Assessment of ‘subgrid’ scale Probability Density Function Models for Large Eddy Simulation

Filtered density functions (FDFs) of mixture fraction are quantified by analyzing experimental data obtained from two-dimensional planar laser-induced fluorescence scalar measurements in the isothermal swirling flow of a combustor operating at a Reynolds number of 28,662 for three different swirl numbers (0.3, 0.58 and 1.07). Two-dimensional filtering using a box filter was performed on the measured scalar to obtain the filtered variables used for presumed FDF for Large Eddy Simulations (LES). A dependant variable from the measured scalar, which was a pre-computed temperature, was integrated over the experimentally obtained FDF as well as over the presumed beta or top-hat FDFs and a relative error in temperature prediction was calculated. The experimentally measured FDFs depended on swirl numbers and axial and radial positions in the flow. The FDFs were unimodal in the regions of low variance and bimodal in the regions of high variance. The influence of the filter spatial dimension on the measured FDF was evaluated and consequences for subgrid modeling for LES discussed

Guided Filtering based Pyramidal Stereo Matching for Unrectified Images

Stereo matching deals with recovering quantitative depth information from a set of input images, based on the visual disparity between corresponding points. Generally most of the algorithms assume that the processed images are rectified. As robotics becomes popular, conducting stereo matching in the context of cloth manipulation, such as obtaining the disparity map of the garments from the two cameras of the cloth folding robot, is useful and challenging. This is resulted from the fact of the high efficiency, accuracy and low memory requirement under the usage of high resolution images in order to capture the details (e.g. cloth wrinkles) for the given application (e.g. cloth folding). Meanwhile, the images can be unrectified. Therefore, we propose to adapt guided filtering algorithm into the pyramidical stereo matching framework that works directly for unrectified images. To evaluate the proposed unrectified stereo matching in terms of accuracy, we present three datasets that are suited to especially the characteristics of the task of cloth manipulations. By com- paring the proposed algorithm with two baseline algorithms on those three datasets, we demonstrate that our proposed approach is accurate, efficient and requires low memory. This also shows that rather than relying on image rectification, directly applying stereo matching through the unrectified images can be also quite effective and meanwhile efficien

OMCat: Catalogue of Serendipitous Sources Detected with the XMM-Newton Optical Monitor

The Optical Monitor Catalogue of serendipitous sources (OMCat) contains entries for every source detected in the publicly available XMM-Newton Optical Monitor (OM) images taken in either the imaging or ``fast'' modes. Since the OM is coaligned and records data simultaneously with the X-ray telescopes on XMM-Newton, it typically produces images in one or more near-UV/optical bands for every pointing of the observatory. As of the beginning of 2006, the public archive had covered roughly 0.5% of the sky in 2950 fields. The OMCat is not dominated by sources previously undetected at other wavelengths; the bulk of objects have optical counterparts. However, the OMCat can be used to extend optical or X-ray spectral energy distributions for known objects into the ultraviolet, to study at higher angular resolution objects detected with GALEX, or to find high-Galactic-latitude objects of interest for UV spectroscopy.Comment: 25 pages, 22 figures, submitted to PAS

Deformable Part Models are Convolutional Neural Networks

Deformable part models (DPMs) and convolutional neural networks (CNNs) are two widely used tools for visual recognition. They are typically viewed as distinct approaches: DPMs are graphical models (Markov random fields), while CNNs are "black-box" non-linear classifiers. In this paper, we show that a DPM can be formulated as a CNN, thus providing a novel synthesis of the two ideas. Our construction involves unrolling the DPM inference algorithm and mapping each step to an equivalent (and at times novel) CNN layer. From this perspective, it becomes natural to replace the standard image features used in DPM with a learned feature extractor. We call the resulting model DeepPyramid DPM and experimentally validate it on PASCAL VOC. DeepPyramid DPM significantly outperforms DPMs based on histograms of oriented gradients features (HOG) and slightly outperforms a comparable version of the recently introduced R-CNN detection system, while running an order of magnitude faster

A Deep Pyramid Deformable Part Model for Face Detection

We present a face detection algorithm based on Deformable Part Models and deep pyramidal features. The proposed method called DP2MFD is able to detect faces of various sizes and poses in unconstrained conditions. It reduces the gap in training and testing of DPM on deep features by adding a normalization layer to the deep convolutional neural network (CNN). Extensive experiments on four publicly available unconstrained face detection datasets show that our method is able to capture the meaningful structure of faces and performs significantly better than many competitive face detection algorithms

Multiparameter vision testing apparatus

Compact vision testing apparatus is described for testing a large number of physiological characteristics of the eyes and visual system of a human subject. The head of the subject is inserted into a viewing port at one end of a light-tight housing containing various optical assemblies. Visual acuity and other refractive characteristics and ocular muscle balance characteristics of the eyes of the subject are tested by means of a retractable phoroptor assembly carried near the viewing port and a film cassette unit carried in the rearward portion of the housing (the latter selectively providing a variety of different visual targets which are viewed through the optical system of the phoroptor assembly). The visual dark adaptation characteristics and absolute brightness threshold of the subject are tested by means of a projector assembly which selectively projects one or both of a variable intensity fixation target and a variable intensity adaptation test field onto a viewing screen located near the top of the housing