We present Large Scale Facial Model (LSFM) - a 3D Morphable (3DMM) automatically constructed from 9,663 distinct facial identities. To the best of our knowledge LSFM is largest-scale ever constructed, containing statistical information huge variety human population. build such large model we introduce novel fully automated and robust construction pipeline. The dataset that trained on includes rich demographic about each subject, allowing for not only global 3DMM but also models tailored...

We present large scale facial model (LSFM)—a 3D Morphable Model (3DMM) automatically constructed from 9663 distinct identities. To the best of our knowledge LSFM is largest-scale ever constructed, containing statistical information a huge variety human population. build such we introduce novel fully automated and robust construction pipeline, informed by an evaluation state-of-the-art dense correspondence techniques. The dataset that trained on includes rich demographic about each subject,...

3D Morphable Models (3DMMs) are powerful statistical models of facial shape and texture, among the state-of-the-art methods for reconstructing from single images. With advent new sensors, many datasets have been collected containing both neutral as well expressive faces. However, all captured under controlled conditions. Thus, even though can be learnt such data, it is difficult to build texture that sufficient reconstruct faces in unconstrained conditions (in-the-wild). In this paper, we...

The Menpo Project, hosted at http://www.menpo.io, is a BSD-licensed software platform providing complete and comprehensive solution for annotating, building, fitting evaluating deformable visual models from image data. powerful flexible cross-platform framework written in Python that works on Linux, OS X Windows. has been designed to allow easy adaptation of Lucas-Kanade (LK) parametric alignment techniques, goes step further all the necessary tools building state-of-the-art such as Active...

3D Morphable Models (3DMMs) are powerful statistical models of facial shape and texture, among the state-of-the-art methods for reconstructing from single images. With advent new sensors, many datasets have been collected containing both neutral as well expressive faces. However, all captured under controlled conditions. Thus, even though can be learnt such data, it is difficult to build texture that sufficient reconstruct faces in unconstrained conditions ("in-the-wild"). In this paper, we...

Establishing inter-mesh dense correspondence is a key step in the process of constructing Morphable Models. The most successful approaches to date reduce this 3D problem 2D image morphing one by applying an interpolant UV space - which manifold face flattened into contiguous atlas. Contiguous spaces are natural products laser scanning devices popular for use Model construction, but wide gamut can now be used capture data that do not yield representation conducive warping. In paper we explore...

Various randomization distributions are shown to arise as conditional in the setting of generalized linear models. These admit saddlepoint approximations which can obviate need simulate they approximate. Examples include multinomial and Dirichlet bootstraps, jackknife, permutation distributions. The double approximation a regular exponential family is be equivalent use single when admits cut.

In many fields, researchers are interested in large and complex biological processes. Two important examples gene expression DNA methylation genetics. One key problem is to identify aberrant patterns of these processes discover biologically distinct groups. this article we develop a model-based method for clustering such data. The basis our involves the construction likelihood any given partition subjects. We introduce cluster specific latent indicators that, along with some standard...

This article considers the problem of sparse estimation canonical vectors in linear discriminant analysis when $p\gg N$. Several methods have been proposed literature that estimate one vector two-group case. However, $G-1$ can be considered if number groups is $G$. In multi-group context, it common to a sequential fashion. Moreover, separate prior covariance structure often required. We propose novel methodology for direct vectors. contrast existing techniques, method estimates all at once,...

Conditional inference eliminates nuisance parameters by conditioning on their sufficient statistics. For contingency tables conditional entails enumerating all with the same statistics as observed data. moderately sized and/or complex models, computing time to enumerate these is often prohibitive. Monte Carlo approximations offer a viable alternative provided it possible obtain samples from correct distribution. This article presents an MCMC extension of importance sampling algorithm, using...

This study investigates the effect of religious identity on U.S. Presidential voter choice in order to determine whether this relationship changed over time. The research literature is divided question with several investigators finding a positive trend religious-political polarization since 1980, and others no polarization. further addresses putative link between social inequality politics by identifying race, class, gender location religiously influenced voters, using multiple cross...

Abstract In standard saddlepoint approximations to the cumulative distribution function of a random variable, normal has appeared play special role. this article we consider what happens when "base" is replaced by an arbitrary base distribution. Generalized versions several formulas, are presented. The choice chi-squared or inverse Gaussian then considered in detail. generalized compared two examples: linear combination variables and first passage time for walk. former example considers...

The program MBBC 2.0 clusters time-course microarray data using a Bayesian product partition model.The model in Booth et al. (2007) simultaneously searches for the optimal number of clusters, and assigns cluster memberships based on temporal changes gene expressions. to makes this method easily available statisticians scientists, is built with three free computer language software packages: Ox, R C++, taking advantage strengths each language. Within MBBC, search algorithm implemented Ox...

Abstract Test statistics for hypotheses about covariance matrices in multivariate analysis of variance have null distributions which are rather intractable to compute. Examples include the modified likelihood ratio statistic testing (i) homogeneity across normal populations (Bartlett-Box M-statistic), (ii) and (iii) simultaneous sphericity covariances populations. This paper provides two saddlepoint approximations each above mentioned test statistics. These result extremely accurate p-value...

The Menpo Project [1] is a BSD-licensed set of tools and software designed to provide an end-to-end pipeline for collection annotation image 3D mesh data. In particular, the provides annotating images meshes with sparse fiducial markers that we refer as landmarks. For example, Figure 1 shows example face has been annotated 68 2D These landmarks are useful in variety areas Computer Vision Machine Learning including object detection, deformable modelling tracking. aims enable researchers,...

This paper discusses characteristics of dye biases in microarray data that the conventional normalization methods do not handle, and proposes a new method involving mixture splines model. We also develop test for between-group comparisons each gene is designed to be used with our proposed method.

It is well known that in a supervised classification setting when the number of features smaller than observations, Fisher's linear discriminant rule asymptotically Bayes. However, there are numerous modern applications where needed high-dimensional setting. Naive implementation this case fails to provide good results because sample covariance matrix singular. Moreover, by constructing classifier relies on all interpretation challenging. Our goal robust only small subset important and...

Very little is known about the theoretical statistical properties of accounting numbers. In this papera probability modelling technique used to analyse volume, efficiency, and price deviation—more usually in literature as ‘variances’—of standard costing. Standard-cost deviations are defined asdifferences between certain types conditional unconditional expected costs. The basic statistics required construct confidence intervals for these differences identified, it shown how formulae normally...