On the Complementarity of Face Parts for Gender Recognition

This paper evaluates the expected complementarity between the most prominent parts of the face for the gender recognition task. Given the image of a face, five important parts (right and left eyes, nose, mouth and chin) are extracted and represented as appearance-based data vectors. In addition, the full face and its internal rectangular region (excluding hair, ears and contour) are also coded. Several mixtures of classifiers based on (subsets of) these five single parts were designed using simple voting, weighted voting and other learner as combiners. Experiments using the FERET database prove that ensembles perform significantly better than plain classifiers based on single parts (as expected)

The Role of Face Parts in Gender Recognition

This paper evaluates the discriminant capabilities of face parts in gender recognition. Given the image of a face, a number of subimages containing the eyes, nose, mouth, chin, right eye, internal face (eyes, nose, mouth, chin), external face (hair, ears, contour) and the full face are extracted and represented as appearance-based data vectors. A greater number of face parts from two databases of face images (instead of only one) were considered with respect to previous related works, along with several classification rules. Experiments proved that single face parts offer enough information to allow discrimination between genders with recognition rates that can reach 86%, while classifiers based on the joint contribution of internal parts can achieve rates above 90%. The best result using the full face was similar to those reported in general papers of gender recognition (>95%). A high degree of correlation was found among classifiers as regards their capacity to measure the relevance of face parts, but results were strongly dependent on the composition of the database. Finally, an evaluation of the complementarity between discriminant information from pairs of face parts reveals a high potential to define effective combinations of classifiers

Face gender classification: A statistical study when neutral and distorted faces are combined for training and testing purposes

This paper presents a thorough study of gender classification methodologies performing on neutral, expressive and partially occluded faces, when they are used in all possible arrangements of training and testing roles. A comprehensive comparison of two representation approaches (global and local), three types of features (grey levels, PCA and LBP), three classifiers (1-NN, PCA + LDA and SVM) and two performance measures (CCR and d′) is provided over single- and cross-database experiments. Experiments revealed some interesting findings, which were supported by three non-parametric statistical tests: when training and test sets contain different types of faces, local models using the 1-NN rule outperform global approaches, even those using SVM classifiers; however, with the same type of faces, even if the acquisition conditions are diverse, the statistical tests could not reject the null hypothesis of equal performance of global SVMs and local 1-NNs

Mirror mirror on the wall... an unobtrusive intelligent multisensory mirror for well-being status self-assessment and visualization

A person’s well-being status is reflected by their face through a combination of facial expressions and physical signs. The SEMEOTICONS project translates the semeiotic code of the human face into measurements and computational descriptors that are automatically extracted from images, videos and 3D scans of the face. SEMEOTICONS developed a multisensory platform in the form of a smart mirror to identify signs related to cardio-metabolic risk. The aim was to enable users to self-monitor their well-being status over time and guide them to improve their lifestyle. Significant scientific and technological challenges have been addressed to build the multisensory mirror, from touchless data acquisition, to real-time processing and integration of multimodal data

Wize Mirror - a smart, multisensory cardio-metabolic risk monitoring system

In the recent years personal health monitoring systems have been gaining popularity, both as a result of the pull from the general population, keen to improve well-being and early detection of possibly serious health conditions and the push from the industry eager to translate the current significant progress in computer vision and machine learning into commercial products. One of such systems is the Wize Mirror, built as a result of the FP7 funded SEMEOTICONS (SEMEiotic Oriented Technology for Individuals CardiOmetabolic risk self-assessmeNt and Self-monitoring) project. The project aims to translate the semeiotic code of the human face into computational descriptors and measures, automatically extracted from videos, multispectral images, and 3D scans of the face. The multisensory platform, being developed as the result of that project, in the form of a smart mirror, looks for signs related to cardio-metabolic risks. The goal is to enable users to self-monitor their well-being status over time and improve their life-style via tailored user guidance. This paper is focused on the description of the part of that system, utilising computer vision and machine learning techniques to perform 3D morphological analysis of the face and recognition of psycho-somatic status both linked with cardio-metabolic risks. The paper describes the concepts, methods and the developed implementations as well as reports on the results obtained on both real and synthetic datasets

Face gender classification under realistic conditions. Dealing with neutral, expressive and partially occluded faces

Esta tesis se centra en la clasificación de género a partir de imágenes faciales tratando el problema con un enfoque más realista que el tradicionalmente utilizado en la literatura. En entornos reales, pueden surgir varios problemas debido a la falta de control sobre los sujetos y su entorno. Además es probable que las características de los individuos, como son su edad y raza, varíen significativamente. Al mismo tiempo, los sujetos pueden manifestar sus emociones mediante expresiones faciales así como llevar puestos complementos que cubran partes de su cara, lo cual provoca que las imágenes faciales contengan ciertas distorsiones. Estos son los principales problemas, junto con otras complicaciones como las causadas por cambios de iluminación y detecciones imprecisas de la cara, que abordamos en este trabajo. Comenzamos estudiando la posibilidad de clasificar el género dadas partes de la cara, como son los ojos, la nariz, la boca y el mentón. A partir de los resultados experimentales que se obtuvieron utilizando dos bases de datos de imágenes faciales, concluimos que los ojos eran la región de la cara que proporcionaba resultados más robustos y que distintas partes de la cara contienen información complementaria sobre el género de la persona. Seguidamente, propusimos un nuevo tipo de características locales y un método de clasificación basado en vecindades. Las características propuestas se basan en valores de contraste locales, aunque manteniendo información espacial. El método de clasificación consiste en una combinación de clasificadores donde cada clasificador base se especializa en una región concreta de la cara. Ambas propuestas se compararon con las técnicas más utilizadas en este campo mediante un completo análisis experimental utilizando imágenes de caras neutras y expresivas y también imágenes de caras con gafas de sol y bufandas. Los resultados empíricos indican que todas las soluciones resuelven la tarea de forma estadísticamente equivalente cuando las imágenes de entrenamiento y test tienen las mismas características. Sin embargo, cuando los conjuntos de entrenamiento y test contienen imágenes de distintos tipos, nuestras propuestas muestran un comportamiento más robusto que el resto. Por último, presentamos un estudio estadístico de la influencia de la resolución de las imágenes en la clasificación de género. Los resultados mostraron que las resoluciones óptimas están entre 22x18 y 90x72 píxeles. Sin embargo, imágenes de sólo 3x2 píxeles proporcionan información útil para comenzar a distinguir entre géneros

The impact of chromosomal fusions on 3D genome folding and recombination in the germ line

The spatial folding of chromosomes inside the nucleus has regulatory effects on gene expression, yet the impact of genome reshuffling on this organization remains unclear. Here, we take advantage of chromosome conformation capture in combination with single-nucleotide polymorphism (SNP) genotyping and analysis of crossover events to study how the higher-order chromatin organization and recombination landscapes are affected by chromosomal fusions in the mammalian germ line. We demonstrate that chromosomal fusions alter the nuclear architecture during meiosis, including an increased rate of heterologous interactions in primary spermatocytes, and alterations in both chromosome synapsis and axis length. These disturbances in topology were associated with changes in genomic landscapes of recombination, resulting in detectable genomic footprints. Overall, we show that chromosomal fusions impact the dynamic genome topology of germ cells in two ways: (i) altering chromosomal nuclear occupancy and synapsis, and (ii) reshaping landscapes of recombination.This work was supported by the Ministry of Economy and Competitiveness (CGL2014-54317-P and CGL2017-83802-P to A.R.-H., BFU2013-47736-P and BFU2017-85926-P to M.A.M.-R. and CGL2010-15243 to J.V.) and the Agència de Gestió d’Ajuts Universitaris i de Recerca, AGAUR (DI2015 and SGR1215 to A.R-H. as well as SGR468 to M.A.M.-R.). C.V. and L.A.-G. were supported by FPI predoctoral fellowships from the Ministry of Economy and Competitiveness (BES-2015-072924 and PRE-2018-083257). L.M.-G. was supported by an FPU predoctoral fellowships from the Ministry of Science, Innovation and University (FPU18/03867). M.A.M.-R. acknowledges support by the European Research Council under the 7th Framework Program FP7/2007-2013 (ERC grant agreement 609989) and the European Union’s Horizon 2020 research and innovation program (grant agreement 676556). A.R.-H. also acknowledges support from MeioNet (BFU2015-71786-REDT)

Three-dimensional genomic structure and cohesin occupancy correlate with transcriptional activity during spermatogenesis

Altres ajuts: Agaur SGR468 to M.A.M-R. A.P.-G. is supported by a 'Doctorats Industrials' predoctoral fellowship (AGAUR). H.H. is a Miguel Servet (CP14/00229) researcher funded by the Spanish Institute of Health Carlos III (ISCIII)Mammalian gametogenesis involves dramatic and tightly regulated chromatin remodeling, whose regulatory pathways remain largely unexplored. Here, we generate a comprehensive high-resolution structural and functional atlas of mouse spermatogenesis by combining in situ chromosome conformation capture sequencing (Hi-C), RNA sequencing (RNA-seq), and chromatin immunoprecipitation sequencing (ChIP-seq) of CCCTC-binding factor (CTCF) and meiotic cohesins, coupled with confocal and super-resolution microscopy. Spermatogonia presents well-defined compartment patterns and topological domains. However, chromosome occupancy and compartmentalization are highly re-arranged during prophase I, with cohesins bound to active promoters in DNA loops out of the chromosomal axes. Compartment patterns re-emerge in round spermatids, where cohesin occupancy correlates with transcriptional activity of key developmental genes. The compact sperm genome contains compartments with actively transcribed genes but no fine-scale topological domains, concomitant with the presence of protamines. Overall, we demonstrate how genome-wide cohesin occupancy and transcriptional activity is associated with three-dimensional (3D) remodeling during spermatogenesis, ultimately reprogramming the genome for the next generation

Three-dimensional genomic structure and cohesin occupancy correlate with transcriptional activity during spermatogenesis

Mammalian gametogenesis involves dramatic and tightly regulated chromatin remodeling, whose regulatory pathways remain largely unexplored. Here, we generate a comprehensive high-resolution structural and functional atlas of mouse spermatogenesis by combining in situ chromosome conformation capture sequencing (Hi-C), RNA sequencing (RNA-seq), and chromatin immunoprecipitation sequencing (ChIP-seq) of CCCTC-binding factor (CTCF) and meiotic cohesins, coupled with confocal and super-resolution microscopy. Spermatogonia presents well-defined compartment patterns and topological domains. However, chromosome occupancy and compartmentalization are highly re-arranged during prophase I, with cohesins bound to active promoters in DNA loops out of the chromosomal axes. Compartment patterns re-emerge in round spermatids, where cohesin occupancy correlates with transcriptional activity of key developmental genes. The compact sperm genome contains compartments with actively transcribed genes but no fine-scale topological domains, concomitant with the presence of protamines. Overall, we demonstrate how genome-wide cohesin occupancy and transcriptional activity is associated with three-dimensional (3D) remodeling during spermatogenesis, ultimately reprogramming the genome for the next generation.This work was supported by the Ministry of Economy and Competitiveness (BFU2017-89408-R to A.M.P.; BFU2013-47736-P and BFU2017-85926-P to M.A.M.-R.; and CGL2014-54317-P and CGL2017-83802-P to A.R.-H.) and the Agència de Gestió d’Ajuts Universitaris i de Recerca (AGAUR) (DI2015 to A.R.-H. and R.A.C., as well as SGR468 to M.A.M-R.). Work at CRG, BIST, and UPF was in part funded by the Spanish Ministry of Economy and Competitiveness, ‘Centro de Excelencia Severo Ochoa 2013-2017’ (SEV-2012-0208), and ‘Centro de Excelencia María de Maeztu 2016-2019.’ CIC-IBMCC is supported by the Programa de Apoyo a Planes Estratégicos de Investigación de Estructuras de Investigación de Excelencia, co-funded by Junta de Castilla y León (CSI239P18) and the European Regional Development Fund (CLC–2017–01). C.V. is supported by a FPI predoctoral fellowship from the Ministry of Economy and Competitiveness (BES-2015-072924). A.P.-G. is supported by a ‘Doctorats Industrials’ predoctoral fellowship (AGAUR). H.H. is a Miguel Servet (CP14/00229) researcher funded by the Spanish Institute of Health Carlos III (ISCIII), the Agencia Estatal de Investigación (AEI), and FEDER (SAF2017-89109-P). C.M. is an Asociación Española Contra el Cáncer (AECC) postdoctoral fellow. M.A.M.-R. acknowledges support by the European Research Council under the 7th Framework Program FP7/2007-2013 (ERC grant agreement 609989) and the European Union’s Horizon 2020 Research and Innovation Programme (grant agreement 676556). A.M.P. and A.R.-H. also acknowledge support from MeioNet (BFU2015-71786-REDT)