人眼识别外文翻译译文
Unit1ArtUsefulwordsandExpressions2课件高中英语人教版选择性
2.如果你能很容易地记住图片、图表和视频中的信息， 你可能是一个视觉学习者。 If you easily remember information from pictures, charts and videos, you are likely a visual learner.
18.guarantee : vt. 保证; 确保; 肯定…必然发 生 n. 保证; 保修 单; 担保物
guarantee sb sth = guarantee sth to sb 向某人保证某事 guarantee to do sth 保证做某事 guarantee sb/sth against/from.. 保证...不受/免遭... give sb a guarantee that... 向某人保证... under guarantee 在保修期内 翻译：1.他们保证在一周内完成这项工作。 They guarantee to finish the work within a week. 2.我们不能保证我们的航班永远不会延误。 We cannot guarantee (that) our flights will never be delayed. 3.努力工作是成功的保证。 Hard work is the guarantee of success. 4.我的表还在保修期内，所以他们会免费修理。
humbly adv. 谦逊地；恭顺地 humbleness n. 谦逊；卑贱 critical adj.批评的；关键的；爱挑刺的 critically adv.批判地；严重地 critic n.批评家；评论家 criticise sb. for (doing) sth. 因（做）某事批评某人 receive/take (accept) criticism: 受到/接受批评 翻译：1.她喜欢在背后批评别人。 She likes to criticise other people behind their backs. 2.日本的决定招致了很多批评。
视觉识别系统英文作文模板
视觉识别系统英文作文模板英文回答：Visual recognition systems (VRS) enable machines to interpret and understand the visual environment, allowing them to identify objects, scenes, and their relationships with a high degree of accuracy. These systems play a crucial role in various applications, such as image and video analysis, object recognition, surveillance, and autonomous driving.VRS typically involve the following components:Image acquisition: Capturing the visual scene using cameras or other sensors.Preprocessing: Enhancing the image quality, removing noise, and extracting relevant features.Feature detection: Identifying distinct featureswithin the image, such as shapes, textures, and edges.Object classification: Classifying the objects present in the image based on their features.Scene understanding: Analyzing the relationships between objects and their context to understand the scene.中文回答：视觉识别系统（VRS）使机器能够解读和理解视觉环境，从而能够以高精度识别物体、场景及其之间的关系。
《眼科学词汇翻译》word版
眼科学词汇翻译ophthalmology, OPH, Ophth 眼科学visionics 视觉学visual optics 视觉光学visual physiology 视觉生理学physiology of eye 眼生理学visual electro physiology 视觉电生理学pathology of eye 眼病理学dioptrics of eye 眼屈光学neuro ophthalmology 神经眼科学ophthalmiatrics 眼科治疗学ophthalmic surgery 眼科手术学cryo ophthalmology 冷冻眼科学right eye, RE, oculus dexter, OD 右眼left eye, LE, oculus sinister, OS 左眼oculus uterque, OU 双眼eyeball phantom 眼球模型eye bank 眼库prevention of blindness, PB 防盲primary eye care 初级眼保健low vision 低视力blindness 盲totol blindness 全盲imcomplete blindness 不全盲congenital blindness 先天性盲acquired blindness 后天性盲曾用名“获得性盲”。
functional blindness 功能性盲organic blindness 器质性盲occupational blindness 职业性盲legal blindness 法定盲visual aura 视觉先兆visual disorder 视觉障碍visual deterioration 视力减退transitional blindness 一过性盲amaurosis 黑●amaurosis fugax 一过性黑●toxic amaurosis 中毒性黑●central amaurosis 中枢性黑●uremic amaurosis 尿毒性黑●cortical blindness 皮质盲macropsia 视物显大症曾用名“大视”。
Face Recognition(人脸识别)
Face RecognitionToday ,I will talk about the study about face recognition.(第二页)As for the face recognition, we main talk about Two-Dimensional Techniques. The study is from The University of York ,Department of Computer Science , as for the date, it is September 2005.(第三页)We say the background.The current identification technology mainly include: fingerprint identification指纹识别, retina recognition视网膜识别, iris recognition虹膜识别, gait recognition步态识别, vein recognition静脉识别, face recognition人脸识别, etc.advantages优点：Compared with other identification methods, face recognition because of its direct, friendly and convenient features, users do not have any psychological barriers, is easy to be accepted by users.(第四页)Two-Dimensional Face Recognition is main about Face Localization.This consists of two stages: face detection（人脸检测）and eye localization（眼睛定位）. (第五页)Today we main study the research of eye localization.Eye localization is performed on the set of training images, which is then separated into two groups. By it, we can compute the average distance from the eye template. one is eye detection was successful (like the picture on), the dark picture means the detected eyes is closed to the eye template; and the other is failed(like the picture down), the bright points down means doesn’t close.(第六页)We do the research using the way: The Direct Correlation Approach（直接相关方法）.This is the way we make the study, you can have a little know about it. So I will not talk much about it.(第七页)This is the study’s main Experimental Process.It is divided into some groups, calculate the distance d, between two facial image vectors, we can get an indication of similarity. Then a threshold is used to make the final verification decision.(第八页)The result wo get the picture. By the picture, we gets an EER (能效比)of 25.1%, this means that one quarter of all verification operations carried out resulted in an incorrect classification. That also means Tiny changes cause the change of the location in image.(第九页)Conclusion: Two-Dimensional Techniques (we say 2D) is an important part in face recognition. It make a large use in face recognition. All in all, Face recognition is the easiest way to be accepted in the identification field.Thank you!。
人脸识别英文专业词汇教学内容
gallery set参考图像集Probe set=test set测试图像集face renderingFacial Landmark Detection人脸特征点检测3D Morphable Model 3D形变模型AAM (Active Appearance Model)主动外观模型Aging modeling老化建模Aging simulation老化模拟Analysis by synthesis 综合分析Aperture stop孔径光标栏Appearance Feature表观特征Baseline基准系统Benchmarking 确定基准Bidirectional relighting 双向重光照Camera calibration摄像机标定（校正）Cascade of classifiers 级联分类器face detection 人脸检测Facial expression面部表情Depth of field 景深Edgelet 小边特征Eigen light-fields本征光场Eigenface特征脸Exposure time曝光时间Expression editing表情编辑Expression mapping表情映射Partial Expression Ratio Image局部表情比率图(,PERI) extrapersonal variations类间变化Eye localization,眼睛定位face image acquisition 人脸图像获取Face aging人脸老化Face alignment人脸对齐Face categorization人脸分类Frontal faces 正面人脸Face Identification人脸识别Face recognition vendor test人脸识别供应商测试Face tracking人脸跟踪Facial action coding system面部动作编码系统Facial aging面部老化Facial animation parameters脸部动画参数Facial expression analysis人脸表情分析Facial landmark面部特征点Facial Definition Parameters人脸定义参数Field of view视场Focal length焦距Geometric warping几何扭曲Street view街景Head pose estimation头部姿态估计Harmonic reflectances谐波反射Horizontal scaling水平伸缩Identification rate识别率Illumination cone光照锥Inverse rendering逆向绘制技术Iterative closest point迭代最近点Lambertian model朗伯模型Light-field光场Local binary patterns局部二值模式Mechanical vibration机械振动Multi-view videos多视点视频Band selection波段选择Capture systems获取系统Frontal lighting正面光照Open-set identification开集识别Operating point操作点Person detection行人检测Person tracking行人跟踪Photometric stereo光度立体技术Pixellation像素化Pose correction姿态校正Privacy concern隐私关注Privacy policies隐私策略Profile extraction轮廓提取Rigid transformation刚体变换Sequential importance sampling序贯重要性抽样Skin reflectance model,皮肤反射模型Specular reflectance镜面反射Stereo baseline 立体基线Super-resolution超分辨率Facial side-view面部侧视图Texture mapping纹理映射Texture pattern纹理模式Rama Chellappa读博计划：1.完成先前关于指纹细节点统计建模的相关工作。
英语口语练习短文：视觉
英语口语练习短文：视觉Vision视觉Human vision like that of other primates has evolved inan arboreal environment. In the dense complex world of a tropical forest, it is more important to see well than to develop an acute sense of smell. In the course of evolution members of the primate line have acquired large eyes whilethe snout has shrunk to give the eye an unimpeded view.人类的视觉，和其它灵长目动物的一样，是在丛林环境中进化出来的。
在稠密、复杂的热带丛林里，好的视觉比灵敏的嗅觉更加重要。
在进化过程中，灵长目动物的眼睛变大，同时鼻子变小以使视野不受防碍。
Of mammals only humans and some primates enjoy color vision. The red flag is black to the bull. Horses live in a monochrome world.Light visible to human eyes however occupies only a very narrow band in the whole electromagnetic spectrum. Ultraviolet rays are invisible to humans though ants and honeybees are sensitive to them. Humans have no direct perception of infrared rays unlike the rattlesnake which has receptors tuned into wavelengths longer than 0.7 micron. The world would look eerily different if human eyes weresensitive to infrared radiation. Then instead of the darkness of night, we would be able to move easily in a strange shadowless world where objects glowed with varying degrees of intensity.在哺乳类动物中，只有人和一些灵长目动物能够分辨颜色。
介绍眼睛英文作文
介绍眼睛英文作文Title: The Window to the Soul: An Exploration of the Human Eye。
The eye, often referred to as the window to the soul,is a marvel of nature's design. Its intricate structure and remarkable function not only enable us to perceive the world around us but also convey a depth of emotion and insight that transcends words. In this essay, we will delve into the fascinating realm of the human eye, exploring its anatomy, physiology, and the profound significance it holds in human experience.At its most basic level, the human eye is a sensory organ responsible for detecting light and converting itinto electrochemical signals that the brain interprets as visual images. Its complex structure consists of several key components, each playing a crucial role in the process of vision. The outermost layer of the eye is the sclera, a tough, protective layer often referred to as the "white" ofthe eye. Within the sclera lies the cornea, a transparent dome-shaped structure that helps to focus light onto the retina.Moving inward, we encounter the iris, the colorful part of the eye that regulates the amount of light entering the eye by adjusting the size of the pupil. Behind the irislies the crystalline lens, which further refracts light to focus it precisely onto the retina. The retina, located at the back of the eye, contains millions of specialized cells called photoreceptors, which convert light into electrical signals that are transmitted to the brain via the optic nerve.But the eye is not merely a sophisticated optical instrument; it is also a potent symbol of human emotion and perception. Shakespeare famously wrote, "The eyes are the windows to the soul," recognizing the profound depth and complexity conveyed through a simple gaze. Indeed, the eyes have the power to express a myriad of emotions – from joy and love to sadness and despair – without uttering a single word. It is through the eyes that we connect withothers on a deeply personal level, conveying empathy, understanding, and compassion.Moreover, the eyes play a central role in nonverbal communication, providing subtle cues that can reveal a person's thoughts, intentions, and feelings. From the fleeting glance of a stranger to the intimate gaze between lovers, our eyes serve as silent messengers, conveying messages that transcend language and cultural barriers.In addition to their role in communication, the eyes also serve as a gateway to our inner world, offering insights into our physical and emotional well-being. Ophthalmologists and optometrists can glean valuable information about a person's health by examining the eyes, detecting signs of diseases such as diabetes, hypertension, and even neurological disorders. Furthermore, changes in eye appearance, such as dilation or discoloration, can be indicative of underlying medical conditions or emotional states.In conclusion, the human eye is a marvel of biologicalengineering, combining exquisite form with unparalleled function. From its intricate anatomy to its profound role in human communication and perception, the eye continues to captivate and inspire us. As we gaze into the eyes of another, we are reminded of the boundless depth and complexity of the human experience, encapsulated within the delicate sphere of vision. Truly, the eye remains a timeless symbol of both our shared humanity and our individual uniqueness.。
visual field名词解释
visual field名词解释Visual field（视野）是指人眼在注视一个固定点时所能观察到的范围。
它是通过眼睛所能接收到的光线来感知周围环境的重要因素之一。
下面是28个双语例句：1. My visual field expanded as I climbed to the top of the mountain.当我爬上山顶时，我的视野扩大了。
2. The doctor tested my visual field to check for any blind spots.医生对我的视野进行了检查，以排除视野中的盲点。
3. The butterfly fluttered into my visual field and caught my attention.蝴蝶飘进了我的视野，引起了我的注意。
4. His peripheral visual field was impaired due to the eye injury.由于眼部受伤，他的周围视野受损。
5. The artist used bold colors to create a sense of depth in his visual field.艺术家运用鲜艳的色彩在他的视野中营造出一种深度感。
6. She noticed a subtle movement in her visual field, but couldn't identify what it was.她注意到视野中有微妙的运动，但无法确定是什么。
7. The driver's impaired visual field contributed to the accident.驾驶员受损的视野导致了这次事故。
8. The athlete's intense focus narrowed his visual field to the finish line.运动员高度集中注意力，将视野缩小到了终点线。
- 1、下载文档前请自行甄别文档内容的完整性，平台不提供额外的编辑、内容补充、找答案等附加服务。
- 2、"仅部分预览"的文档,不可在线预览部分如存在完整性等问题,可反馈申请退款(可完整预览的文档不适用该条件!)。
- 3、如文档侵犯您的权益，请联系客服反馈,我们会尽快为您处理(人工客服工作时间：9:00-18:30)。
译文：惺忪眼睛识别之睡意检测林信锋，林家仁，姚志国立东华大学，台湾花莲摘要：随着科学技术和汽车工业的进步，道路上有了越来越多的车辆。
其结果是，繁忙的交通经常导致越来越多的交通事故。
普通交通事故，司机注意力不集中通常是一个主要原因。
若要避免这种情况，本文提出了惺忪的眼识别系统的嗜睡检测。
首先，级联Adaboost算法与Haar特征分类器来找出人脸。
第二，眼睛区域位于主动形状模型（ASM）搜索算法。
然后采用二进制的模式和边缘检测的眼睛特征提取和确定眼睛的状态。
实验结果表明即使没有系统训练阶段也能与其他方法的性能比较。
关键词：人脸检测；人眼识别；睡意。
一、引言在过去的几十年中，随着车辆技术的发展交通事故发生率越来越高。
驾驶员疲劳驾驶被认为是一个重要因素。
许多研究显示长时间驾驶的危险是相当于醉酒驾驶。
因此，驾驶员疲劳驾驶已成为一个普遍的问题。
其结果是，大量的研究一直致力于检测系统的不安全驾驶。
安全驾驶系统可以概括为两大类。
一种是车辆的"以车为本"的 [1] [2] 方法，其中着重论述，如车辆的道路上，位置状态变化的速度，等等。
另一类是"以人为本"的方法，侧重于驱动程序的状态。
此方法分析了驱动程序的人脸图像与图像处理和模式识别，如眨眼频率和眼睛关闭 [3] 的时间。
提出的方法基于这一类别。
林 et al.[4] 评估几个功能集和分类对于亲密关系的人眼检测。
他们采用灰度值，Gabor 小波、局部二进制模式（LBP）及直方图的面向梯度（HOG）来表示功能集，并与三种类型的分类器（即，邻近取样（NN），支持向量机（SVM）和 Adaboost算法）比较。
实验结果表明，各种特征描述符的结合大大提高了精度。
吴吴 et al.[5] 提出了一种识别眼睛的状态方法。
他们用 haar 特征和Adaboost 分类器 [6] 来找出人脸区域。
LBP 被考虑作为图像的特征和特点采用支持向量机训练。
然后利用支持向量机识别眼睛的状态。
他们证明了该方法能有效地检测司机睡意，通过计算 PERCOLS （眼闭百分比）。
在本文中，我们提出惺忪的眼识别系统训练阶段无睡意检测。
一个级联的Adaboost 分类器 haar 特征 [7] 与主动形状模型（ASM） [8] 用于找出人脸定位和眼区。
然后采用二进制的模式和边缘检测的眼睛特征提取和确定眼睛的状态。
实验结果与其它的方法，有训练阶段将演示的性能比较。
本文的结构如下。
第 2 节中，描述了拟议的方法。
节 3 演示实验结果。
最后，第 4 节中得出结论。
二.拟议的方法提出的方法具有四个主要步骤： 1）图像预处理；2）人脸检测；3）眼睛检测；4）的眼睛的状态识别。
图 1 说明了驾驶员瞌睡侦测系统的流程图。
在下面的小节提出了所提出方法的细节。
图一：该算法的流程图。
A.图像预处理亮度变化会影响系统的精确率。
因此，提出的方法都最初适用光补偿的直方图均衡化 [9]。
在此步骤中，图 2 中所示我们分为红色、绿色和蓝色分量的彩色图像，分别适用于每个组件的直方图均衡化。
然后得到补偿的图像。
光的补偿，我们降低了补偿图像的分辨率，以提高系统的效率。
图二：光补偿的直方图均衡方案B.人脸检测级联的 Adaboost 分类器 haar 特征 [10] 利用，找出人脸区域。
第一，补偿的图像分割成矩形区域，在任何位置和原始图像中的刻度数。
由于人脸面部特征的差异，haar 特征是有效的实时人脸检测。
这些可以根据不同的矩形区域内的像素值的总和计算。
如图 3 所示，可以由不同组成的黑色区域和白色区域表示功能。
级联的 Adaboost 分类器是一个强分类器相结合的几个弱分类器。
每个弱分类器的Adaboost 算法训练。
如果候选人样品通过级联的 Adaboost 分类器，可以发现人脸区域。
几乎所有的脸样本可以通过和非人脸样本会被拒绝。
图 4 显示的人脸检测与级联的Adaboost 分类器。
abc图 3:Haar 特征： (a) 边缘特性线 (b) (c) 中心-包围功能图 4:与级联的 Adaboost 分类器的人脸检测C.眼检测主动形状模型（ASM） [8] 是一种基于统计学习模型的人脸特征提取算法。
它的目的是以匹配新的图像模型。
在拟议的方法中，ASM 被训练从面部的轮廓与一组手动标记的点。
然后算法选择主要变化训练数据中的主成分分析（PCA）方法。
建立 ASM 后, 眼睛定位得到如图 5 所示。
图 5:检测结果的人脸区域和眼睛的位置D.表彰的眼睛的状态眼睛的特征提取识别眼睛的状态。
一般情况下，左眼状态等于权利一在同一时间。
因此，我们只考虑在一个框架中的一只眼睛状态。
这种考虑也是有益于降低了计算复杂度。
在此步骤中，通过了两项计划：（1）二元模式和 (2) Canny 边缘检测 [11]。
眼图像转换为二进制模式基于阈值 t。
n xTni i ∑==1( 1 )（1） n 是像素在眼部和 x 我的号码是该位置的像素值在该地区。
眼部有 n 像素为单位）。
如果 P 的像素值大于阈值 T ，P 将设置为白色，1。
否则 P 将被设置为 0。
它的定义 （2） 所示。
{,),(,1.),(,0),(T y x gray T y x gray y x p ≥<=( 2 ) 图 6 显示了一些二进制模式的睁眼和闭的眼。
完成的眼图像转换后，眼睑的高度被用于确定眼睛的状态。
图 6。
二进制模式： （a)-(b)开眼和 （c)-(d) 闭眼Canny 边缘检测算法很出名的是它能够生成连续的边缘。
首先，图像平滑的高斯卷积。
),(*),(),(g y x G y x I y x σ=(3)2222)(221),(σσπσy x e y x G +-=(4)在σ那里是尺度参数。
然后，通过差分滤波计算出的大小和方向的边缘。
通过多尺度边缘信息获得最终的边缘图像。
最后，边缘点的号被总结识别眼睛的状态。
三.实验结果在实验中，' 眨眼个人主页数据库 ' [12] 采用绩效进行评价。
它包含 80 20 个人的 AVI 格式的视频剪辑。
有四种类型的剪辑： 1）正面视图不戴眼镜，2）正面视图和薄的金边眼镜，3）正面视图和黑框眼镜，4）向上视图不戴眼镜。
每个个体以正常的速度闪烁，一个视频剪辑的不同 1 至 6 倍。
一些框架如图 7 所示。
图 7：四种类型的个人主页眨眼数据库我们可以适用 SPSS 绘制 ROC （接收机经营特点）曲线，实验的图 8 所示。
然后计算 AUC （曲线下面积）值，97.4%。
闭着眼睛，睁开眼睛的识别率列在表一、表二所显示的识别率和 AUC 相比 [4]。
它被指出我们的结果优于某些现有的方法进行训练阶段。
此外，我们的方法的性能比较被获得未经训练阶段。
图8：roc曲线表一：准确率和LBP及支持向量机的比较表二：与【4】的性能比较四、结论本文介绍了惺忪的眼识别嗜睡检测未经训练阶段。
开始的时候，用 haar 特征 Adaboost 分类器是应用，找出人脸区域。
然后眼睛区域位于 ASM。
最后，采用二进制的模式和边缘检测识别眼睛的状态。
实验结果证明该方法可以准确地检测困倦的眼睛。
此外，性能比较表明无训练阶段的识别系统是有用的驾驶员睡意检测。
确认本文的研究是通过利用 '眨眼个人主页数据库' [12] 完成的。
我们深深地感谢团队提供完整的数据库。
引用[1] I Isabelle Tang and Toby P.Breckon., “Automatic Road Environment Classification,” IEEE Transactions on Intelligent Transportation Systems, vol. 12, no. 2, pp. 476-484, June 2011[2] P. Jansen, W. van der Mark, J. C. van den Heuvel, and F. C. A. G roen , “Colour based off-road environment and terrin type classification,” Proceedings of the 8th International IEEE Conference on Intelligent Transportation Systems, pp. 216–221,2005.[3] Inho Choi, Seungchul Han, and Daijin Kim, “Eye Detection and Eye Bl ink Detection using Adaboost Learning and Grouping,” Proceedings of the 20 th International Conference on ICCCN, 2012.[4] Xue Liu, Xiaoyang Tan, and Songcan Chen, “ Eye Closeness Detection Using Appearance Based Methods,” Intelligent Information Pro cessing, volume 385 of IFIP Advances in Information and Communication Technology, pp. 398-408, 2012.[5] Yu-Shan Wu, Ting-Wei Lee, Quen-Zong Wu and Heng-Sung Liu, “An Eye State Recognition Method for Drowsiness Detection” The 71st IEEE International Confer ence onVehicular Technology Conference (VTC 2010-Spring).[6] Jerome Friedman, Trevor Hastie and Robert Tibshirani, “Additive Logistic Regression: A statistical View of Boosting”, The Annals of Statistics, vol. 28, no. 2, pp. 377-407, 2002.[7] Vladimi Pa vlovic and Ashutosh Garg, “Efficient Detection of Objects and Attributes using Boosting,” IEEE Conf. Computer Vision and Pattern Recognition, 2001.[8] Stephen J. McKenna, Yogesh Raja and Shaogang Gong, “Tracking Colour Objects Using Adaptive Mixture Model s”, Image and Vision Computing, pp225~231, March 1999.[9] Hojat Yeganeh, Ali Ziaei and Amirhossein Rezaie, “A Novel Approach for Contrast Enhancement Based on Histogram Equalization.” Proceedings of the International Conference on Computer and Communication Engineering, 2008.[10] P. Viola and M. Jones, “Rapid object detection using a boosted cascade of simple feature”, Proceeding of the 2011 IEEE Computer Society Conference, vol.1, pp.I-511~I-518, 2001.[11] Canny, John “A Computational Approach to Edge Detection”, IEEE Transactions on Pattern Analysis and Machine Intelligent, vol. PAMI- 8, no. 6, November 1986.[12] Gen Pan, Lin Sun, Zhaohui Wu and Shihong Lao, “Eyeblink-based Antispoofing in Face Recognition from a Generic Web-camera”, The 11th IEE International Conference on Computer Vision (ICCV’07), Rio de Janeiro, Brazil, October 14-20, 2007。