基于Eigenfaces方法的人脸检索

基于主成分分析的特征脸方法是人脸识别中的重要算法之一,本文提出利用特征脸对高考考生免冠照片进行相似度比对的检索方法,为验证提出方法的实用性和有效性,利用特征脸方法和考生照片库设计了人脸图像检索原型系统并进行了实验,实验结果表明本文方法能够有效检索出相似度较高的考生照片,具有一定的应用价值和研究意义。

Human Friendly Interface Design for Virtual Fitting Room Applications on Android Based Mobile Devices

This paper presents an image processing design flow for virtual fitting room (VFR) applications, targeting both personal computers and mobile devices. The proposed human friendly interface is implemented by a three-stage algorithm: Detection and sizing of the user's body, detection of reference points based on face detection and augmented reality markers, and superimposition of the clothing over the user's image. Compared to other existing VFR systems, key difference is the lack of any proprietary hardware components or peripherals. Proposed VFR is software based and designed to be universally compatible as long as the device has a camera. Furthermore, JAVA implementation on Android based mobile systems is computationally efficient and it can run in real-time on existing mobile devices.

A Novel Wavelet Image Coding Method Incorporating with Human Face Detection

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A closed-loop algorithm to detect human face using color and reinforcement learning

A closed-loop algorithm to detect human face using color information and reinforcement learning is presented in this paper. By using a skin-color selector, the regions with color "like" that of human skin are selected as candidates for human face. In the next stage, the candidates are matched with a face model and given an evaluation of the match degree by the matching module. And if the evaluation of the match result is too low, a reinforcement learning stage will start to search the best parameters of the skin-color selector. It has been tested using many photos of various ethnic groups under various lighting conditions, such as different light source, high light and shadow. And the experiment result proved that this algorithm is robust to the vary-ing lighting conditions and personal conditions.

RETRACTED:<i>Realization of Virtual Human Face Based on Deep Convolutional Generative Adversarial Networks</i>

Short Retraction Notice The authors claim that this paper needs modifications. This article has been retracted to straighten the academic record. In making this decision the Editorial Board follows COPE's Retraction Guidelines. The aim is to promote the circulation of scientific research by offering an ideal research publication platform with due consideration of internationally accepted standards on publication ethics. The Editorial Board would like to extend its sincere apologies for any inconvenience this retraction may have caused. Editor guiding this retraction: Prof. Baozong Yuan(EiC of JSIP) The full retraction notice in PDF is preceding the original paper, which is marked "RETRACTED".

A Human Face Recognition Method based on the Core Characteristics under the Condition of Illumination

A core characteristics based human face recognition method under the condition of illumination is proposed according to the problem of the sharply declining human face recognition rate under the condition of lighL With this method, if human face image is affected by light and the illumination is forward or side can be judged; the images affect by illumination are processed using the strategy of frequency domain replacement, and then the key areas of human face image are divided and then are recognized using support vector machine （SVM） based on the unit of area, and finally the recognition results are integrated. The experimental result shows that this method can produce a better recognition effect than other methods in view of the problem of illumination.

FUNCTIONAL MAPPING OF THE HUMAN BRAIN DURING ACUPUNCTURE WITH MAGNETIC RESONANCE IMAGINGSOMATOSENSORY CORTEX ACTIVATION

Hegu (LI 4) is one of the most frequently used and most important analgesic points in Chinese acupuncture. It is particularly effective for treating disorders of the head and face. According to the meridian theory in Traditional Chinese Medicine (TCM), the Large Intestine Meridian to which it belongs originates in the hand and terminates in the face. This theory is based, however, more on thousands of years of clinical experience rather than on scientific evidence. In our study of acupuncture effects on normal human volunteers with the non-invasive BOLD (blood oxygenation level dependant)technique for FMRI (functional magnetic resonance imaging), we demonstrated widespread effects in the brain during acupuncture at Hegu and Zusanli (ST 36). A finding of special interest was observed in the primary somatosensory cortes (SI) during Hegu acupuncture. In additlon to activation of the area representing the hand in response to the sensory impulses arising from the site of stimulation, activation also occurred in the face representation in all 3 subjects brains studied by coronal brain sections. In one of these subjects activation in the face representation was even stronger than that in the hand representation. Areas representing the neck, trunk and other parts of the upper extremity also exhibited increase in signal intensity, subject to individual variability. As compared with Hegu, such effects were either absent or much weaker with acupuncture at Zusanli (ST 36) or with other forms of sensory stimulation to the hand. Functional mapping of the brain with MRI has provided the first direct evidence in support of the important role of Hegu acupuncture in TCM.

Robust video foreground segmentation and face recognition

Face recognition provides a natural visual interface for human computer interaction （HCI） applications. The process of face recognition, however, is inhibited by variations in the appearance of face images caused by changes in lighting, expression, viewpoint, aging and introduction of occlusion. Although various algorithms have been presented for face recognition, face recognition is still a very challenging topic. A novel approach of real time face recognition for HCI is proposed in the paper. In view of the limits of the popular approaches to foreground segmentation, wavelet multi-scale transform based background subtraction is developed to extract foreground objects. The optimal selection of the threshold is automatically determined, which does not require any complex supervised training or manual experimental calibration. A robust real time face recognition algorithm is presented, which combines the projection matrixes without iteration and kernel Fisher discriminant analysis （KFDA） to overcome some difficulties existing in the real face recognition. Superior performance of the proposed algorithm is demonstrated by comparing with other algorithms through experiments. The proposed algorithm can also be applied to the video image sequences of natural HCI.

基于Metaface字典学习与核稀疏表示的人脸识别方法

完备的稀疏表示方法近年来应用在人脸识别中并取得较好的结果,它可以仅利用样本的随机投影完成对测试样本的识别。在实际应用中,由于受光照、遮挡等因素的影响,测试样本并不能通过训练样本的线性组合得到很好的稀疏重构。本文提出了基于Metaface字典学习与核稀疏表示的人脸识别方法,借助核技巧,将数据样本和字典集映射到高维的未知空间,以解决特征的非线性相似问题。在核空间对数据样本进行稀疏重构,得到数据在核空间的一种简洁的稀疏表达方式从而提高识别率,而Metaface字典学习框架的引入可以得到更加精炼的字典,从全局上提高识别率。通过在ORL人脸库、Yale人脸库和AR人脸库的实验表明,同等情况下,本文提出的方法优于PCA,SVM,SRC等方法,进一步提高了人脸识别率,具有较好的应用价值。

Face Detection and Localization in Color Images: An Efficient Neural Approach

Automatic face detection and localization is a key problem in many computer vision tasks. In this paper, a simple yet effective approach for detecting and locating human faces in color images is proposed. The contribution of this paper is twofold. First, a particular reference to face detection techniques along with a background to neural networks is given. Second, and maybe most importantly, an adaptive cubic-spline neural network is designed to be used to detect and locate human faces in uncontrolled environments. The experimental results conducted on our test set show the effectiveness of the proposed approach and it can compare favorably with other state-of-the-art approaches in the literature.

Prevalence and Severity of Current Human-Elephant Conflicts in Amboseli Ecosystem, Kenya: Insights from the Field and Key Informants

Few animals elicit such drastically different human emotions, so do elephants. Elephants capture the affection of people but also inspire animosity and fear at the same time. This is because there are conflicts with people over space, critical resources, costs of damages and general insecurity to people. This paper examined field evidence and interviewed expert key informants on current intensity and frequency of human-elephants in Amboseli Ecosystem. According to them, generally, the most prevalent (score of 1 lowest to 10 highest) threats to elephants were competition for critical resources (6.32 ± 0.44) followed by blocking of migration (6.24 ± 0.46), harassment of elephants (4.83 ± 0.75), poaching (4.57 ± 0.37), and retaliatory killings (3.78 ± 0.31). For threats that elephants pose to people, the most prevalent one was crop raiding (6.95 ± 0.26) followed by environmental degradation (6.71 ± 0.46), general insecurity to people (5.76 ± 0.65), property destruction (5.16 ± 0.41), injury and death to livestock (3.78 ± 0.37), and injury and death to people (2.71 ± 0.27). For the severity of the threats, the highest score was given to crop raiding whose average score was 7.90 ± 0.24 followed by environmental destruction and degradation (6.89 ± 0.43), injury and death to people (6.72 ± 0.44), injury and death to livestock (6.36 ± 0.50), property destruction (5.78 ± 0.49), general insecurity to people (5.62 ± 0.64). Severity levels followed the same trend or varied slightly. These drivers of human-elephant conflicts need to be addressed decisively to protect both people and elephants. There is a need to ensure local people’s benefit from elephants through ecotourism investments such as wildlife sanctuaries, leasing critical space for elephants’ dispersal on acceptable terms, through appropriate compensation schemes for elephant costs, and supporting local community wildlife rangers to prevent conflicts.

Stuck with the Sur-face： An Ethical Approach to Facial Disfigurement in Willa Cather＇s ＂The Profile＂

The human face consists of three dimensions： （1） the visible, static sur-face, （2） the mobile dimension, which communicates thoughts, emotions, and states of mind, and （3） the invisible dimension, the face aspars-pro-toto for the whole person who owns the face. In this latter sense, the human face is at the center of Emmanuel Levinas＇ theory of ethics： We encounter each other face-to-face, he argues, and it is the other＇s face that calls for my ethical response to the holiness of his/her wholeness and essence. The primary ethical imperative is： ＂Thou shalt not kill.＂ When we encounter a facially disfigured person, we usually fail to respond ethically because we concentrate on the disfigurement. The second dimension, as a result of the disfigurement, is often impaired and thus incapable of communicating in such a way that we can ＂read＂ the face. With our gaze fixed on the disfigured part of the face, we lose sight of the person as a whole. Metaphorically speaking, we could even say that we ＂kill＂ the person. Levinas conceives of the other＇s face not in its plastic manifestation. But the encounter with the other does at first take place as embodiment. According to Merleau-Ponty, this encounter is by definition interactive and dialogical. In Willa Cather＇s short story ＂The Profile,＂ young beautiful Virginia marries a portrait painter after he has finished her portrait in profile. The left side of her face is severely disfigured because of a burn. Her husband is waiting impatiently for her to talk about ＂it＂ and the suffering it must cause her in order to ＂heal＂ her with his love, but she behaves as if it did not exist and even likes to dress extravagantly. In the following analysis of the short story, it will be illustrated how the husband fails to respond to his wife＇s face＇s invitation to interact with it and get in touch with the wholeness of her person that it stands for. Instead, he reduces her to the disfigurement. When he finally names the scar, he metaphorically ＂kills＂ her, as well as their marriage.

Campus Intelligence Mental Health Searching System Based on Face Recognition Technology

The phenomenon of teenage campus suicide has become the focus of attention of parents,schools and the society.The causes behind it are extremely complicated,and the root cause is psychological and spiritual problems.However,one's negative psychology is often hidden,and it is difficult to detect and effectively intervene before the tragedy.How to effectively identify students with suicidal tendencies in order to prevent tragedies has aroused extensive research and discussion among the government,academia and the public.Through investigation and research,it is found that the current popular computer cutting-edge technologies such as artificial intelligence and computer vision can be well used for human emotion recognition and behavior prediction,and put into use in schools as a mental health auxiliary diagnosis and treatment system,thus effectively reducing the suicide rate on campus.The scenario assumes that machine learning can be used to deduce the risk of psychological problems in human samples by analyzing the frequency of negative emotions in facial expressions.Based on this,this paper proposes an effective solution for campus suicide prediction,and designs a set of auxiliary diagnosis and treatment system based on campus monitoring network system for suicide behavior prediction and student mental health analysis.Through preliminary experimental analysis and verification,the suicide psychological auxiliary diagnosis and treatment system has achieved good results in face recognition success rate,emotion recognition success rate and behavior prediction success rate.With the input of more experimental data and the increase of self-training time,the prediction system will perform better.

Campus Intelligence Mental Health Searching System Based on Face Recognition Technology

The phenomenon of teenage campus suicide has become the focus of attention of parents,schools and the society.The causes behind it are extremely complicated,and the root cause is psychological and spiritual problems.However,one’s negative psychology is often hidden,and it is difficult to detect and effectively intervene before the tragedy.How to effectively identify students with suicidal tendencies in order to prevent tragedies has aroused extensive research and discussion among the government,academia and the public.Through investigation and research,it is found that the current popular computer cutting-edge technologies such as artificial intelligence and computer vision can be well used for human emotion recognition and behavior prediction,and put into use in schools as a mental health auxiliary diagnosis and treatment system,thus effectively reducing the suicide rate on campus.The scenario assumes that machine learning can be used to deduce the risk of psychological problems in human samples by analyzing the frequency of negative emotions in facial expressions.Based on this,this paper proposes an effective solution for campus suicide prediction,and designs a set of auxiliary diagnosis and treatment system based on campus monitoring network system for suicide behavior prediction and student mental health analysis.Through preliminary experimental analysis and verification,the suicide psychological auxiliary diagnosis and treatment system has achieved good results in face recognition success rate,emotion recognition success rate and behavior prediction success rate.With the input of more experimental data and the increase of self-training time,the prediction system will perform better.

Logics of Constructing Chinese Form of Human Civilization Facing the Future:CPC and Development of Chinese Culture

As one of the oldest human civilizations,the Chinese nation once created brilliant ancient and classical culture.However,in transition to modernity,as China became a late comer of modernization,the Chinese nation has chosen the Party as the leading force in constructing its modern culture.Guided by Marxism,the Communist Party of China(CPC)has advanced

融合视觉图像处理的目标识别技术在移动机器人中的应用

为了提升移动机器人的运动人体识别效果,研究利用Faster-RCNN-KF对动态人体图像进行实时跟踪,并结合Facenet-MTCNN实现跟踪对象人脸识别。运动人体跟踪检测实验和人脸识别测试结果显示,Faster-RCNN-KF算法跟踪误差仅为0.000 5 m,且跟踪响应速度和误差更正速度较快;Facenet-MTCNN目标识别算法在训练中的分类精度最高能够达到99.15%,分类中的时间延迟为0.01 s,能够有效识别跟踪对象的身份信息。研究结果表明,视觉图像处理技术能够实现人体的有效跟踪检测,并能对不同身份的跟踪对象进行人脸识别,对移动机器人跟踪与识别技术发展具有重要价值。

基于改进稠密网络的视频监控人脸识别算法研究

为了提升视频监控中的人脸识别能力,研究利用运动历史图像算法来实现人体跟踪,提出了一种改进稠密网络。在结果中显示,研究采用的人体跟踪算法的跟踪准确率高达99.5%,同时提出的识别算法的识别准确率能够稳定在99.7%以上,且能够针对不同表情特征的人脸表现出较高的识别准确率。以上结果表明,改进稠密网络能够有效提升视频监控人脸识别能力,对城市监控的智能化发展具有重要意义。

数字说话人脸生成技术综述

在现代计算机视觉和自然语言处理的交叉领域,数字说话人脸生成技术已经成为一个越来越重要的研究主题。数字说话人脸生成技术专注于依据预定的文本或音频序列生成逼真的人脸图像。近年来,深度学习方法,如卷积神经网络、生成对抗性网络以及神经渲染场在此领域已经表现出了显著的应用价值。这些方法不仅引起了学术界的广泛关注,而且在工业界得以实际应用,用于解决图像处理和计算机视觉方面的具体问题。尽管已经取得了一定的进展,实际应用这些方法仍然面临诸多挑战。综合分析和评估深度学习方法在数字说话人脸生成方面的具体实现,以识别现存方法的优缺点,探讨尚待解决的普遍问题,并突出仍需进一步研究的开放性问题。此外,从统计学角度列出了目前可用的数据集,并对其进行评估和比较,以便研究人员能更容易地选择满足他们需求的数据集。

浅析电影《刮痧》中西文化冲突

随着经济全球化进程日益增快,各国文化交流需求更加迫切。由于中西文化差异,国际交往过程中难免出现冲突与碰撞。电影《刮痧》是中西方跨文化交际过程中的小缩影,再现了华裔在美国遇到的文化冲突。本文旨在通过电影所表现的文化冲突对中西方在面子观、朋友观、亲情观、儿童人权观以及法律文化方面进行比较分析,体现中西方文化共性和差异,并提出中西方文化融合的趋势和必然。求同存异是世界文化交流的基本准则,这样各国文化才能更好地传承与发展。

基于人脸识别的人力资源远程线上考勤系统

随着员工工作业务范围的扩大,对考勤系统的应用提出了更高要求,为此基于人脸识别设计研究人力资源远程线上考勤系统。从人脸信息采集、人脸信息存储与处理及远程线上通信三个模块入手,设计并合理配置。在系统软件设计方面,分别设计人脸信息处理、人脸识别与考勤数据库模块,实现人力资源远程线上考勤系统的运行。实验结果表明:所提系统获得考勤员工的人脸识别相较对比系统,时延更短、错误率更低,系统应用性能较佳。