From 3D Point Clouds to Pose-Normalised Depth Maps

We consider the problem of generating either pairwise-aligned or pose-normalised depth maps from noisy 3D point clouds in a relatively unrestricted poses. Our system is deployed in a 3D face alignment application and consists of the following four stages: (i) data filtering, (ii) nose tip identification and sub-vertex localisation, (iii) computation of the (relative) face orientation, (iv) generation of either a pose aligned or a pose normalised depth map. We generate an implicit radial basis function (RBF) model of the facial surface and this is employed within all four stages of the process. For example, in stage (ii), construction of novel invariant features is based on sampling this RBF over a set of concentric spheres to give a spherically-sampled RBF (SSR) shape histogram. In stage (iii), a second novel descriptor, called an isoradius contour curvature signal, is defined, which allows rotational alignment to be determined using a simple process of 1D correlation. We test our system on both the University of York (UoY) 3D face dataset and the Face Recognition Grand Challenge (FRGC) 3D data. For the more challenging UoY data, our SSR descriptors significantly outperform three variants of spin images, successfully identifying nose vertices at a rate of 99.6%. Nose localisation performance on the higher quality FRGC data, which has only small pose variations, is 99.9%. Our best system successfully normalises the pose of 3D faces at rates of 99.1% (UoY data) and 99.6% (FRGC data)

Geodesics on the manifold of multivariate generalized Gaussian distributions with an application to multicomponent texture discrimination

We consider the Rao geodesic distance (GD) based on the Fisher information as a similarity measure on the manifold of zero-mean multivariate generalized Gaussian distributions (MGGD). The MGGD is shown to be an adequate model for the heavy-tailed wavelet statistics in multicomponent images, such as color or multispectral images. We discuss the estimation of MGGD parameters using various methods. We apply the GD between MGGDs to color texture discrimination in several classification experiments, taking into account the correlation structure between the spectral bands in the wavelet domain. We compare the performance, both in terms of texture discrimination capability and computational load, of the GD and the Kullback-Leibler divergence (KLD). Likewise, both uni- and multivariate generalized Gaussian models are evaluated, characterized by a fixed or a variable shape parameter. The modeling of the interband correlation significantly improves classification efficiency, while the GD is shown to consistently outperform the KLD as a similarity measure

Validation of northern latitude Tropospheric Emission Spectrometer stare ozone profiles with ARC-IONS sondes during ARCTAS: sensitivity, bias and error analysis

We compare Tropospheric Emission Spectrometer (TES) versions 3 and 4, V003 and V004, respectively, nadir-stare ozone profiles with ozonesonde profiles from the Arctic Intensive Ozonesonde Network Study (ARCIONS, http://croc.gsfc.nasa.gov/arcions/ during the Arctic Research on the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) field mission. The ozonesonde data are from launches timed to match Aura's overpass, where 11 coincidences spanned 44° N to 71° N from April to July 2008. Using the TES "stare" observation mode, 32 observations are taken over each coincidental ozonesonde launch. By effectively sampling the same air mass 32 times, comparisons are made between the empirically-calculated random errors to the expected random errors from measurement noise, temperature and interfering species, such as water. This study represents the first validation of high latitude (>70°) TES ozone. We find that the calculated errors are consistent with the actual errors with a similar vertical distribution that varies between 5% and 20% for V003 and V004 TES data. In general, TES ozone profiles are positively biased (by less than 15%) from the surface to the upper-troposphere (~1000 to 100 hPa) and negatively biased (by less than 20%) from the upper-troposphere to the lower-stratosphere (100 to 30 hPa) when compared to the ozonesonde data. Lastly, for V003 and V004 TES data between 44° N and 71° N there is variability in the mean biases (from −14 to +15%), mean theoretical errors (from 6 to 13%), and mean random errors (from 9 to 19%)

The O2 A-band in fluxes and polarization of starlight reflected by Earth-like exoplanets

Earth-like, potentially habitable exoplanets are prime targets in the search for extraterrestrial life. Information about their atmosphere and surface can be derived by analyzing light of the parent star reflected by the planet. We investigate the influence of the surface albedo $A_{\rm s}$, the optical thickness $b_{\rm cloud}$ and altitude of water clouds, and the mixing ratio $\eta$ of biosignature O$_2$ on the strength of the O$_2$ A-band (around 760 nm) in flux and polarization spectra of starlight reflected by Earth-like exoplanets. Our computations for horizontally homogeneous planets show that small mixing ratios ($\eta$ < 0.4) will yield moderately deep bands in flux and moderate to small band strengths in polarization, and that clouds will usually decrease the band depth in flux and the band strength in polarization. However, cloud influence will be strongly dependent on their properties such as optical thickness, top altitude, particle phase, coverage fraction, horizontal distribution. Depending on the surface albedo, and cloud properties, different O$_2$ mixing ratios $\eta$ can give similar absorption band depths in flux and band strengths in polarization, in particular if the clouds have moderate to high optical thicknesses. Measuring both the flux and the polarization is essential to reduce the degeneracies, although it will not solve them, in particular not for horizontally inhomogeneous planets. Observations at a wide range of phase angles and with a high temporal resolution could help to derive cloud properties and, once those are known, the mixing ratio of O$_2$ or any other absorbing gas.Comment: 21 pages, 20 figures, accepted for publication in Ap

Effective retrieval and new indexing method for case based reasoning: Application in chemical process design

In this paper we try to improve the retrieval step for case based reasoning for preliminary design. This improvement deals with three major parts of our CBR system. First, in the preliminary design step, some uncertainties like imprecise or unknown values remain in the description of the problem, because they need a deeper analysis to be withdrawn. To deal with this issue, the faced problem description is soften with the fuzzy sets theory. Features are described with a central value, a percentage of imprecision and a relation with respect to the central value. These additional data allow us to build a domain of possible values for each attributes. With this representation, the calculation of the similarity function is impacted, thus the characteristic function is used to calculate the local similarity between two features. Second, we focus our attention on the main goal of the retrieve step in CBR to find relevant cases for adaptation. In this second part, we discuss the assumption of similarity to find the more appropriated case. We put in highlight that in some situations this classical similarity must be improved with further knowledge to facilitate case adaptation. To avoid failure during the adaptation step, we implement a method that couples similarity measurement with adaptability one, in order to approximate the cases utility more accurately. The latter gives deeper information for the reusing of cases. In a last part, we present a generic indexing technique for the base, and a new algorithm for the research of relevant cases in the memory. The sphere indexing algorithm is a domain independent index that has performances equivalent to the decision tree ones. But its main strength is that it puts the current problem in the center of the research area avoiding boundaries issues. All these points are discussed and exemplified through the preliminary design of a chemical engineering unit operation

Remote sensing of tropical tropopause layer radiation balance using A-train measurements

Determining the level of zero net radiative heating (LZH) is critical to understanding parcel trajectory in the Tropical Tropopause Layer (TTL) and associated stratospheric hydration processes. Previous studies of the TTL radiative balance have focused on using radiosonde data, but remote sensing measurements from polar-orbiting satellites may provide the relevant horizontal and vertical information for assessing TTL solar heating and infrared cooling rates, especially across the Pacific Ocean. CloudSat provides a considerable amount of vertical information about the distribution of cloud properties relevant to heating rate analysis. The ability of CloudSat measurements and ancillary information to constrain LZH is explored. We employ formal error propagation analysis for derived heating rate uncertainty given the CloudSat cloud property retrieval algorithms. Estimation of the LZH to within approximately 0.5 to 1 km is achievable with CloudSat, but it has a low-altitude bias because the radar is unable to detect thin cirrus. This can be remedied with the proper utilization of Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) lidar backscatter information. By utilizing an orbital simulation with the GISS data set, we explore the representativeness of non-cross-track scanning active sounders in terms of describing the LZH distribution. In order to supplement CloudSat, we explore the ability of Atmospheric Infrared Sounder (AIRS) and Advanced Microwave Scanning Radiometer-EOS (AMSR-E) to constrain LZH and find that these passive sounders are useful where the cloud top height does not exceed 7 km. The spatiotemporal distributions of LZH derived from CloudSat and CALIPSO measurements are presented which suggest that thin cirrus have a limited effect on LZH mean values but affect LZH variability