Fast Landmark Localization with 3D Component Reconstruction and CNN for Cross-Pose Recognition

Two approaches are proposed for cross-pose face recognition, one is based on the 3D reconstruction of facial components and the other is based on the deep Convolutional Neural Network (CNN). Unlike most 3D approaches that consider holistic faces, the proposed approach considers 3D facial components. It segments a 2D gallery face into components, reconstructs the 3D surface for each component, and recognizes a probe face by component features. The segmentation is based on the landmarks located by a hierarchical algorithm that combines the Faster R-CNN for face detection and the Reduced Tree Structured Model for landmark localization. The core part of the CNN-based approach is a revised VGG network. We study the performances with different settings on the training set, including the synthesized data from 3D reconstruction, the real-life data from an in-the-wild database, and both types of data combined. We investigate the performances of the network when it is employed as a classifier or designed as a feature extractor. The two recognition approaches and the fast landmark localization are evaluated in extensive experiments, and compared to stateof-the-art methods to demonstrate their efficacy.Comment: 14 pages, 12 figures, 4 table

L'Auto-vélo : automobilisme, cyclisme, athlétisme, yachting, aérostation, escrime, hippisme / dir. Henri Desgranges

28 février 19251925/02/28 (A26,N8841)

Additional file 7 of On the impact of relatedness on SNP association analysis

SNP selection of HapMap genotype data. This file contains a list of HapMap SNP identifiers used for our analyses. rsid (reference SNP identifier) refers to the first column of the genotype data files as provided by HapMap. (CSV 10000 kb

Additional file 10 of On the impact of relatedness on SNP association analysis

Comparison of methods for modelling the polygenic effect. This file provides additional tables with inflation results for different polygenic models. (PDF 67 kb

Additional file 9 of On the impact of relatedness on SNP association analysis

Comparison of different degrees of heritability. This file contains additional tables with inflation results for different degrees of heritability. (PDF 75 kb

Additional file 2 of On the impact of relatedness on SNP association analysis

Theoretical background. This file provides the theoretical background and derivations of equations presented in the manuscript. (PDF 231 kb

Additional file 6 of On the impact of relatedness on SNP association analysis

Sample selection of HapMap genotype data. This file provides annotations for 174 HapMap CEU samples. The columns FID (family identifier), IID (individual identifier), dad, mom, sex (1=male, 2=female), pheno (always 0), population (always CEU) correspond to the columns of relationships_w_pops_121708.txt filtered for CEU samples as provided by HapMap. The column ctr contains a unique trio identifier and equals NA when the sample does not belong to a complete trio family. The reason for exclusion is provided where applicable, otherwise NA is stated and the sample is included in our study. (CSV 8 kb

Additional file 4 of On the impact of relatedness on SNP association analysis

Preparation of HapMap data. This document provides details regarding the filtering of samples and SNPs of the HapMap data. (PDF 97 kb

Retroelements and the human genome: New perspectives on an old relation

Retroelements constitute a large portion of our genomes. One class of these elements, the human endogenous retroviruses (HERVs), is comprised of remnants of ancient exogenous retroviruses that have gained access to the germ line. After integration, most proviruses have been the subject of numerous amplifications and have suffered extensive deletions and mutations. Nevertheless, HERV-derived transcripts and proteins have been detected in healthy and diseased human tissues, and HERV-K, the youngest, most conserved family, is able to form virus-like particles. Although it is generally accepted that the integration of retroelements can cause significant harm by disrupting or disregulating essential genes, the role of HERV expression in the etiology of malignancies and autoimmune and neurologic diseases remains controversial. In recent years, striking evidence has accumulated indicating that some proviral sequences and HERV proteins might even serve the needs of the host and are therefore under positive selection. The remarkable progress in the analysis of host genomes has brought to light the significant impact of HERVs and other retroelements on genetic variation, genome evolution, and gene regulation