Aproximação fisionômica pericial através de função de base radial hermitiana

A aproximação fisionômica é o método que busca, a partir do crânio, simular a fotografia de um indivíduo quando em vida. Deve ser empregada como último recurso, na busca de desaparecidos, quando não houver possibilidade de aplicação de um método válido de identificação. O objetivo deste estudo foi obter a aproximação fisionômica, a partir de um crânio seco e de tomografia computadorizada multislice de indivíduos vivos, através da função de base radial hermitiana (FBRH). Constituiu-se também em avaliar o resultado da mesma quanto ao reconhecimento. Na primeira etapa do estudo, foi utilizada a imagem escaneada de um crânio seco, de origem desconhecida, com o intuito de avaliar se a quantidade de pontos obtidos seria suficiente para aplicação da FBRH e consequente reconstrução da superfície facial. Na segunda fase, foram utilizadas três tomografias de indivíduos vivos, para análise da semelhança alcançada entre a face escaneada e as aproximações faciais. Nesta etapa, foi aplicada uma associação de diferentes metodologias já publicadas, para reconstrução de uma mesma região da face, a partir de um mesmo crânio. Na última etapa, foram simuladas situações de reconhecimento com familiares e amigos dos indivíduos doadores das tomografias. Observou-se que a metodologia de FBRH pode ser empregada em aproximação fisionômica. Houve reconhecimento positivo nos três sujeitos estudados, sendo que, em dois deles, os resultados foram ainda mais significativos. Desta forma, conclui-se que a metodologia é rápida, objetiva e proporciona o reconhecimento. Esta permite a criação de múltiplas versões de aproximações fisionômicas a partir do mesmo crânio, o que amplia as possibilidades de reconhecimento. Observou-se ainda que a técnica não exige habilidade artística do profissional.

Origin and dispersal of atypical aldehyde dehydrogenase ALDH2*487Lys

The East Asian respond with a marked facial flushing and mild to moderate symptoms of intoxication after drinking the amounts of alcohol that has no detectable effect on European. The alcohol sensitivity in Orientals is due to a delayed oxidation of aceta

Opengazer: open-source gaze tracker for ordinary webcams

Opengazer is an open source application that uses an ordinary webcam to estimate head pose, facial gestures, or the direction of your gaze. This information can then be passed to other applications. For example, used in conjunction with Dasher, opengazer allows you to write with your eyes. Opengazer aims to be a low-cost software alternative to commercial hardware-based eye trackers. The first version of Opengazer was developed by Piotr Zieliński, supported by Samsung and the Gatsby Charitable Foundation. Research and development for Opengazer has been continued by Emli-Mari Nel, and was supported until 2012 by the European Commission in the context of the AEGIS project, and also by the Gatsby Charitable Foundation.

Learning based automatic face annotation for arbitrary poses and expressions from frontal images only

Statistical approaches for building non-rigid deformable models, such as the Active Appearance Model (AAM), have enjoyed great popularity in recent years, but typically require tedious manual annotation of training images. In this paper, a learning based approach for the automatic annotation of visually deformable objects from a single annotated frontal image is presented and demonstrated on the example of automatically annotating face images that can be used for building AAMs for fitting and tracking. This approach employs the idea of initially learning the correspondences between landmarks in a frontal image and a set of training images with a face in arbitrary poses. Using this learner, virtual images of unseen faces at any arbitrary pose for which the learner was trained can be reconstructed by predicting the new landmark locations and warping the texture from the frontal image. View-based AAMs are then built from the virtual images and used for automatically annotating unseen images, including images of different facial expressions, at any random pose within the maximum range spanned by the virtually reconstructed images. The approach is experimentally validated by automatically annotating face images from three different databases. © 2009 IEEE.

A method of Biomimetic Pattern Recognition for face recognition

A new method of face recognition, based on Biomimetic Pattern Recognition and Multi-Weights Neuron Network, had been proposed. A model for face recognition that is based on Biomimetic Pattern Recognition had been discussed, and a new method of facial feature extraction also had been introduced. The results of experiments with BPR and K-Nearest Neighbor Rules showed that the method based on BPR can eliminate the error recognition of the samples of the types that not be trained, the correct rate is also enhanced.

Investigation on molecular and crystal structures of metal complexes with aminopolycarboxylic acids .1. Synthesis and structure of Na-2[Fe-III(ida)(2)](2)center dot 3H(2)O

The crystal structure of the title complex salt has been determined by single-crystal X-ray structure analysis. The crystal data areas follows; Monoclinic, P2(1)/c, a=15.6480(10)Angstrom, b=16.7870(10)Angstrom, c=10.347(2)Angstrom, beta=90.790(10), V=2717.7(6)Angstrom(3), Z=3, and R=0.0333 for 4789 unique reflections. The complex anion has a pseudo-octahedral structure distorted more than the Cr-III and Co-III analogs, in which each, iminodiacetato ligand (ida(2-)) is coordinated in a facial fashion with the two N atoms in a cis configuration, resulting in an unsym-fac structure.

Second-order solutions for random interfacial waves in N-layer density-stratified fluid with steady uniform currents

In the present paper, the random inter facial waves in N-layer density-stratified fluids moving at different steady uniform speeds are researched by using an expansion technique, and the second-order a symptotic solutions of the random displacements of the density interfaces and the associated velocity potentials in N-layer fluid are presented based on the small amplitude wave theory. The obtained results indicate that the wave-wave second-order nonlinear interactions of the wave components and the second-order nonlinear interactions between the waves and currents are described. As expected, the solutions include those derived by Chen (2006) as a special case where the steady uniform currents of the N-layer fluids are taken as zero, and the solutions also reduce to those obtained by Song (2005) for second-order solutions for random interfacial waves with steady uniform currents if N=2.

改进的统计不相关最优鉴别矢量集

该文对统计不相关最优鉴别矢量集算法进行研究,在分析统计不相关最优鉴别矢量集算法的基础上提出了一种改进的方法。该方法在类内散布矩阵的特征空间中求解统计不相关最优鉴别矢量集。为了加快特征抽取速度,利用基于图像鉴别分析的维数压缩方法,对图像数据进行了压缩。在ORL和Yale人脸数据库的数值实验,验证本文所提出的方法的有效性。

基于模糊神经网络的人脸识别方法研究

人脸识别是模式识别研究领域的重要课题,具有广阔的应用前景。本文提出了基于模糊神 经网络的人脸识别方法。首先用最优鉴别分析方法提取人脸的最优鉴别矢量集,构成特征空间,然后在 特征空间中设计模糊神经网络分类器。在ORL人脸图象库上的实验结果表明了该方法的有效性。

统计不相关最佳鉴别矢量集的本质研究

对统计不相关最佳鉴别矢量集的本质进行研究 ,在基于总体散布矩阵特征分解的基础上 ,构造了一种白化变换 ,使得变换后的样本空间中的总体散布矩阵为单位矩阵 ,这样使得传统的最佳鉴别矢量集算法得到的均是具有统计不相关的最佳鉴别矢量集 ,从而揭示了统计不相关最佳鉴别变换的本质———白化变换加普通的线性鉴别变换。该方法的最大优点在于所获得的最优鉴别矢量同时具有正交性和统计不相关性。该方法对代数特征抽取具有普遍适用性。用ORL人脸数据库的数值实验 ,验证了该方法的有效性

基于扰动方法的广义最佳鉴别矢量集求解的一种迭代算法

本文对广义最佳鉴别矢量的求解方法进行研究 ,根据矩阵的扰动理论 ,改进了郭提出的求解广义最佳鉴别矢量的一种迭代算法 ,提出了求解广义最佳鉴别矢量的一种新的迭代算法 .本文算法的一个突出优点是随着类别数目的增加 ,计算时间反而缩短 ;而老算法随着类别数目的增加计算时间随着增加 ;不仅如此 ,新算法的识别率不劣于老算法 .在 ORL人脸数据库的数值实验 ,验证了上述论断的正确性

面孔身份与面部表情识别中的区分度效应

Whether facial identity and facial expression was processed independently has long been a controversy. Studies at levels of experimental, neuropsychological, functional imaging and cell-recording all failed to consistently support either independent or interdependent processing. Present study proposed that familiarity and discriminability of facial identity and expression was important variable in mediating the relation between facial identity and facial expression recognition. Effects of familiarity on recognition of facial identity and expression had been examined (e.g. Ganel & Goshen-Gottstein, 2004) but the role of the discriminability in recognition of facial identity and expression has not yet been carefully examined. To examine the role of discriminability of facial identity and expression, 8 experiments were conducted with Garner’s speeded classification task in recognition of identity and expression of unfamiliar faces. The discriminability of facial identity and expression was manipulated, and the measurements of Garner interference and facilitation indicated that: 1. The discriminability of facial identity and expression mediate the relation between facial identity and expression recognition. Four possible discriminability combinations between identity and expression predicted 4 interference patterns between them. Low discriminability accounted for the interference either in facial identity judgment or in facial expression judgment task. 2. The measurements of eye movements indicated that either in facial identity or in facial expression recognition low discriminability led to a narrowly-distributed eye fixation pattern while high discriminability led to a widely-distributed eye fixation pattern. 3. By combining the morphing technique with the Garner paradigm, study 2 successfully demonstrated the linar relation between discriminability and Garner facilitation effects, confirmed the discriminability effects in the measurements of Garner facilitation effects.. 4. By providing the varying information of facial expression, study 2 revealed that varying information improved the discriminability of facial expression, and then enhanced the recognition of facial expression. All the results indicated that the discriminability of facial identity and expression could mediate the independent or interdependent processing between them, and the discriminability effects on recognition of identity and expression of unfamiliar faces was identified. The results from interference effects and facilitation effects both indicated that the dimensional relation between facial identity and expression was separable but not asymmetric claimed by previous studies（Schweinberger et al, 1998, 1999）. Absolutedly independent or interdependent processing between facial identity and expression recognition were both impossible, discriminability of identity and expression mediated the relation between them. The discriminability effects revealed in present study could explain the conflicts between existing findings well.

精神分裂症患者及其未患病一级亲属的面孔情绪知觉研究

Schizophrenia is a heritable disorder. However, molecular genetics and related research area have not unmasked the nature and mechanisms of this disorder. Therefore, many researchers begin to explore the pathology mechanism from other approaches. High-risk study is one of the promising approaches. In this study, we mainly focused on facial emotion perception in schizophrenia and their non-psychotic first-degree relatives, and attempted to explore whether facial emotion perception is the potential biological marker of schizophrenia. This dissertation comprises 4 studies. In the first study, we conducted a meta-analysis on behavioral data of facial emotion perception in schizophrenia. Our findings showed that patients demonstrated general deficits in both facial emotion perception and facial processing tasks. In the second study, sixty-nine patients with schizophrenia and 56 of their first-degree relatives (33 parents and 23 siblings), and 92 healthy controls (67 younger and 25 older healthy controls) completed a set of facial emotion perception tasks. The results validated that patients with schizophrenia displayed general deficits in facial emotion perception. Study two also demonstrated that siblings of patients performed equally well compared to the corresponding younger healthy controls in all the facial emotion perception tasks, while the parents of patients behaved significantly worse than the corresponding older healthy controls in the composite index of facial emotion perception tasks. The results suggest that relatives of patients display more severely declining in facial emotion perception with the increasing of age. In the third study, we used an automated voxel-wise technique, activation likelihood estimation (ALE) to provide an objective, quantitative evaluation of facial emotion processing in schizophrenia. Our findings demonstrated a marked under-recruitment of the amygdala, accompanied by a substantial limitation in activation in schizophrenia throughout a ventral temporal-basal ganglia-prefrontal cortex ‘social-brain’ system may be central to the difficulties patients experience when processing facial emotion. In the last study, we did an fMRI study about facial emotion perception in 12 patients with schizophrenia, 12 non-psychotic siblings of patients and 12 healthy controls. The results suggest that siblings of patients demonstrate abnormal activation in a variety of brain areas, including prefrontal gyrus, insula, parahippocampal gyrus and superior temporal gyrus. Taken together, the current findings suggest facial emotion perception may be a potential biological marker of schizophrenia.

Estimation of Pose and Illuminant Direction for Face Processing

In this paper three problems related to the analysis of facial images are addressed: the illuminant direction, the compensation of illumination effects and, finally, the recovery of the pose of the face, restricted to in-depth rotations. The solutions proposed for these problems rely on the use of computer graphics techniques to provide images of faces under different illumination and pose, starting from a database of frontal views under frontal illumination.

Vectorizing Face Images by Interpreting Shape and Texture Computations

The correspondence problem in computer vision is basically a matching task between two or more sets of features. In this paper, we introduce a vectorized image representation, which is a feature-based representation where correspondence has been established with respect to a reference image. This representation has two components: (1) shape, or (x, y) feature locations, and (2) texture, defined as the image grey levels mapped onto the standard reference image. This paper explores an automatic technique for "vectorizing" face images. Our face vectorizer alternates back and forth between computation steps for shape and texture, and a key idea is to structure the two computations so that each one uses the output of the other. A hierarchical coarse-to-fine implementation is discussed, and applications are presented to the problems of facial feature detection and registration of two arbitrary faces.