Description: 人耳识别技术是20世纪90年代末开始兴起的一种生物特征识别技术，与其它生物特征识别技术比较具有以下几个特点：（1）与人脸识别方法比较，耳识别方法不受面部表情、化妆品和胡须变化的影响，同时保留了面部识别图象采集方便的优点，与人脸相比，整个人耳的颜色更加一致、图像尺寸更小，数据处理量也更小。（2）与指纹识别方法比较，耳图象的获取是一种被动方式，即通过非接触方式获取耳图像，不存在通过接触传染疾病的机会，因此，其信息获取方式具有容易被人接受的优点。（3）与虹膜识别方法比较，首先，由于人脸和头发的存在，需要在耳识别过程中增加一个耳区域定位步骤，这并不影响耳特征的提取，而眼毛对虹膜的遮挡将直接影响虹膜特征的提取。头发对于耳的遮挡可以容易地避免，而眼毛对于虹膜的遮挡是生理结构决定的，也是难以避免的。其次，就目前的技术而言，虹膜采集需要测试者与采集装置之间的位置在机器发出的语言提示下进行不断地调整，同时要瞪大眼睛，使虹膜尽可能暴露，初试者通常要反复多次调整才能够达到要求，而耳采集方式与脸采集方式基本相同，测试者很容易达到拍摄图象的要求条件。最后，虹膜采集装置的成本要高于耳采集装置。-ear recognition technology of the 20th century, the beginning of the end of the 1990s the rise of a biometric identification technology, and other biometric identification technology compared with the following characteristics : (1) and face recognition methods, Ear Recognition from facial expressions, cosmetics and beards change, while retaining a facial recognition image acquisition convenience advantages, and face, the ears of the whole person more consistent color. Image size is smaller, the amount of data processing are even smaller. (2) and fingerprint identification methods, the ear image acquisition is a passive way, through non-contact ear acquire images, and there is no disease transmitted by the opportunity, therefore, its way to obtain information is easily accepted advantages. Platform: |
Size: 202752 |
Author:蒋建军 |
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Description: 为了更准确地识别人的表情，在识别人脸7 种基本表情（愤怒、厌恶、恐惧、高兴、无表情、悲伤和惊讶）时，采用了局域二值
模式技术提取面部特征，进行由粗略到精细的表情分类。在粗略分类阶段，7 种基本表情中的2 种表情被选为初步分类结果（候选表情）。
在精细分类阶段，选用计算加权卡方值确定最终分类结果。采用日本的Jaffe 表情数据库来验证算法性能，对陌生人表情的识别率为77.9％，
其结果优于采用同样数据库的其他方法，且易于实现-In order to more accurately identify the person s facial expressions, in the identification of seven kinds of basic facial expressions (anger, disgust, fear, happy, expressionless, sadness and surprise), the use of local binary pattern of facial features extraction techniques, carried out by the rough to the fine expression classification. In the rough classification stage, the seven kinds of basic expressions in the two kinds of expression was selected as the initial classification results (candidate expressions). In the fine classification stage, the choice of calculating the weighted chi-square value to determine the final classification results. Jaffe expressions used in Japan to validate algorithm performance database of strangers face recognition rate was 77.9, the result is better than using the same database in other ways, and are easy to achieve Platform: |
Size: 212992 |
Author:张波 |
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Description: 人脸识别论文：《采用Adaboost算法进行面部表情识别》《动态权值预划分实值Adaboost人脸检测算法》《改进的AdaBoost分类器在视频中的体育场景检测》-Face recognition thesis: the use of Adaboost algorithm to identify facial expressions, dynamic weight pre-classified real Adaboost face detection algorithm, Improved AdaBoost classifier of sports in the video scene detection Platform: |
Size: 520192 |
Author:王云 |
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Description: 人表情判断的代码，用vc++写的。
expressiondb是表情库，请放于硬盘盘根目录下。
test1是程序，运行即可。-Human facial expressions to determine the code, using vc++ Written. expressiondb is the expression library, please put in the hard disk root directory. test1 is the procedure to run. Platform: |
Size: 751616 |
Author:koman |
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Description: Face Transfer is a method for mapping videorecorded perfor-mances of one individual to facial animations of another. It extracts visemes (speech-related mouth articulations), expressions, and three-dimensional (3D) pose from monocular video or 铿乴m footage. Platform: |
Size: 14246912 |
Author:Andrey |
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Description: 擅 蔓：以人脸的表情识别为实验背景， 分析了在对人脸表情的识别过程中，单个独立分薰对识别率的影响，由此进一步总结了在表情识
别中如何更有效地选取独立子空间，以实现在不影响识别率的前提下，减少用于构成独立子空问所需的独立分量的个数。 独立成分分析；表情识别；独立子空间 -Good man: Face to face identification for the experimental background, the analysis of facial expressions in the identification process, a single smoked separate the impact of the recognition rate, thus further summarized in the expression recognition of how to more effectively select the independent sub-space in order to achieve the recognition rate does not affect the premise, for constituting a separate sub-reducing space required for the number of independent component. Independent component analysis expression recognition independent subspace Platform: |
Size: 272384 |
Author:金振东 |
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Description: 基于遗传算法和bp网络的简单人脸识别，只能识别三种表情。图像经过简单的小波变换处理-Bp networks based on genetic algorithm and a simple face recognition, could only identify three kinds of expressions. After a simple wavelet transform image processing Platform: |
Size: 1042432 |
Author:王平 |
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Description: Real-Time Facial Feature Point Extraction-Localization of facial feature points is an important step for many subsequent facial image analysis tasks. In this paper, we proposed a new coarse-to-fine method for extracting 20 facial feature points from image sequences. In particular, the Viola-Jones face detection method is extended to detect small-scale facial components with wide shape variations, and linear Kalman filters are used to smoothly track the feature points by handling detection errors and head rotations. The proposed method achieved higher than 90 detection rate when tested on the BioID face database and the FG-NET facial expression database. Moreover, our method shows robust performance against the variation of face resolutions and facial expressions. Platform: |
Size: 871424 |
Author:Ng Jack |
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Description: A very good paper that explain tracking facial feature under varying face pose and facial expression-This paper presents a hierarchical multi-state pose-dependent approach for facial feature detection and tracking under varying facial expression and face pose. For effective and efficient representation of feature points, a hybrid representation that integrates Gabor wavelets and gray-level profiles is proposed. To model the spatial relations among feature points, a hierarchical statistical face shape model is proposed to characterize both the global shape of human face and the local structural details of each facial component. Furthermore, multi-state local shape models are introduced to deal with shape variations of some facial components under different facial expressions. During detection and tracking, both facial component states and feature point positions, constrained by the hierarchical face shape model, are dynamically estimated using a switching hypothesized measurements (SHM) model. Experimental results demonstrate that the proposed method accurately and robustly tracks faci Platform: |
Size: 958464 |
Author:Ng Jack |
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Description: Deaf people use facial expressions a non-manual channel for conveying grammatical information in sign language. Tracking facial features using the Kanade - Lucas - Tomasi (KLT) algorithm is a simple and effective method toward recognizing these facial expressions, which are performed simultaneously with head motions and hand signs. To make the tracker robust under these conditions, a Bayesian framework was developed as a feedback mechanism to the KLT tracker. This mechanism relies on a set of face shape subspaces learned by Probabilistic Principal Component Analysis. An update scheme was utilized to modify these subspaces and adapt to persons with different face shapes. The result shows that the proposed system can track facial features with large head motions, substantial facial deformations, and temporary face occlusions by hand.-Deaf people use facial expressions as a non-manual channel for conveying grammatical information in sign language. Tracking facial features using the Kanade- Lucas- Tomasi (KLT) algorithm is a simple and effective method toward recognizing these facial expressions, which are performed simultaneously with head motions and hand signs. To make the tracker robust under these conditions, a Bayesian framework was developed as a feedback mechanism to the KLT tracker. This mechanism relies on a set of face shape subspaces learned by Probabilistic Principal Component Analysis. An update scheme was utilized to modify these subspaces and adapt to persons with different face shapes. The result shows that the proposed system can track facial features with large head motions, substantial facial deformations, and temporary face occlusions by hand. Platform: |
Size: 189440 |
Author:Ng Jack |
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Description: Running this funciton each time to compute the LBP-TOP distribution of one video sequence.
Reference:
Guoying Zhao, Matti Pietikainen, "Dynamic texture recognition using local binary patterns
with an application to facial expressions," IEEE Transactions on Pattern Analysis and Machine
Intelligence, 2007, 29(6):915-928.-It is 3D LBP, which is publised in IEEE TPAMI, a top journal of computer vision and pattern recognition.
After unzipping the package, you can find a project coded in C++. After complied it, you can use it directly. Some tested images are also attached in the package. Platform: |
Size: 1819648 |
Author:zhang hong |
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Description: This a software utility. It provides auto attendance management system using face detection technique. Now a day’s many utilities provide face detection system but not intelligent. Our project is more intelligent, cost less and very easy to configure anywhere.
Human face detection is the most important process in applications such as video surveillance, human computer interface, face recognition, and image database management. Face detection algorithms have primary factors that decrease a detection ratio : variation by lighting effect, location and rotation, distance of object, complex background. Due to variations in illumination, background, visual angle and facial expressions, the problem of machine face detection is complex. -This is a software utility. It provides auto attendance management system using face detection technique. Now a day’s many utilities provide face detection system but not intelligent. Our project is more intelligent, cost less and very easy to configure anywhere.
Human face detection is the most important process in applications such as video surveillance, human computer interface, face recognition, and image database management. Face detection algorithms have primary factors that decrease a detection ratio : variation by lighting effect, location and rotation, distance of object, complex background. Due to variations in illumination, background, visual angle and facial expressions, the problem of machine face detection is complex.
Platform: |
Size: 2751488 |
Author:minu |
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Description: Face and micro expression analysis book, Describes the various emotions and expressions that are used as lie detectors. Platform: |
Size: 1134592 |
Author:Vishal |
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Description: 论文提出一种全自动识别人脸七种基本表情(愤怒、厌恶、恐惧、高兴、无表情、悲伤和惊奇)的方法。该方法首先
采用几何模型匹配法自动定位出人眼，在此基础上进行人脸大小归一化，然后利用局域二值模式(Local Binary Pattern．
LBP)技术提取面部特征，最后采用由粗到细的方案进行表情分类。采用日本的JAFFE公用表情数据库来检测算法的性
能，实验结果验证了方法的有效性。-Paper proposes a fully automatic identification of seven basic facial expressions (anger, disgust, fear, happy, neutral, sadness, and surprise) method. In this method, the geometric model matching method with automatic positioning to human eyes, in this based on the human face of Size Normalization and then use local binary pattern (Local Binary Pattern. LBP) Jishu extract facial features, and finally using coarse-to- fine program expression classification. Public expression of Japan' s JAFFE database performance detection algorithm, experimental results verify the validity of the method. Platform: |
Size: 171008 |
Author:MJ |
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Description: 完整的表情识别系统一般包括人脸表情图像捕获、预处理、人脸检测与定位、
人脸分割与归一化、人脸表情特征提取、人脸表情识别。本文着重研究了人脸表
情特征提取、特征选择及表情分类等关键问题，并提出了一些改进的方法，同时
进行了仿真实验-Complete expression recognition systems typically include facial expression image capture, preprocessing, face detection and location, face segmentation and normalization, facial expression feature extraction, facial expression recognition. Paper focuses on the facial expression feature extraction, feature selection and classification of facial expressions and other key issues and put forward a number of improved methods, and simulation experiment Platform: |
Size: 1054720 |
Author:KW |
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Description: aleix@ecn.
Semantic queries to a database of images are more
desirable than low-level feature queries, because they
facilitate the user s task. One such approach is the
object-related image retrieval. In the context
people s names and facial expressions. However, when
images of the database are allowed to appear at dif-
ferent facial expressions, the face recognition approach
encounters the expression-invariant problem, i.e. how
to robustly identify a person s face for which its learn- Platform: |
Size: 357376 |
Author:a v |
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Description: ORL人脸库，可以用于人脸检测识别用，在 ORL 人脸库中，有 400 幅分辨率为92*112，具有不同表情、不同姿势、稍许倾斜(不超过20度)、稍许遮掩的图像-ORL face database, face detection and recognition can be used for the ORL face database, there are 400 92* 112 resolution, with different expressions, different posture, a slight tilt (not more than 20 degrees), slightly obscured Image Platform: |
Size: 3082240 |
Author:sunny |
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Description: 高独特性特征的选择以及合适匹配策略的选用是人脸识别技术的关键。讨论了基于仿射不变的几何特
征SIFT算子进行人脸识别的方法。SIFT算子的计算复杂度较高，并且不同的人脸表情和图像模糊会加大特征匹
配的难度。为克服上述缺点，提出了一种新的算法，将选择6个人脸上感兴趣子区域进行描述，并根据各自的独特
性赋予不同的权值，最后在匹配过程中使用相似度的平方来减小偏差数据造成的影响。实验结果表明，该方法能
有效减轻表情变化对于身份识别率急剧下降的影响，并可显著减少计算复杂度和特征匹配时间。-Choosing a distinctive feature and matching criterion is key to developing a reliable face recognition system．
This paper discusses the availability of one of geometric feature invariants，scale invariant feature transform (SIFT)
descriptor based face recognition． The SIFT feature description of an image is typically complex． In most cases， the
difficulty of feature matching problem is aggravated when the diferent face expressions and image blur exist． For
abovementioned issues，in this paper we proposes a new method that six interest sub—regions from the face are selected to be
described and later be calculated through diferent weights according to their distinctiveness．The square of the similarity is
used to solve the problem of data deviation．The experimental results demonstrate that our method does effectively moderate
the face expression efect． It also successfully reduces the complexity and matching time of SIFT feature sets． Platform: |
Size: 286720 |
Author:陈方芳 |
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Description: 本程序实现了用贝叶斯实现人脸表情的识别，很精确的结果，具有很高的识别效果-This application implements with bayesian realize face expressions of the recognition, very accurate results, has the very high recognition result Platform: |
Size: 48128 |
Author:sun |
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Search - face expressions