Description: 針對單一人臉做出五官的檢測定位,並在人臉上畫出五官的方框作為表示.-For a single human face detection features make positioning, and his face painted in the box as an express facial features. Platform: |
Size: 3072 |
Author:李毅駿 |
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Description: 对由光源颜色变化引起的图像色彩偏差,进行了校正,并在YCbCr颜色空间建立了Cb-Cr色度查找表和亮度信息联合的肤色模型,应用预处理技术,去除部分非人脸区域,减少人脸检测的搜索空间,并采用模板匹配方法在人脸候选区域检测人脸.实验表明,该方法能够有效的从复杂环境的彩色图像中检测出左右旋转不超过45°的人脸,且不受人脸表情、尺度和数目的影响,且错误率较低.-Color by the light source caused by the change of image color deviation, a correction, and YCbCr color space established a Cb-Cr chrominance and luminance information look-up table of the color model of the joint application of pre-treatment technology, to remove some non-human face region, Face detection to reduce the search space, using a template matching method in the face candidate region detection of human faces. experiments show that the method can be effective in complex environments from color images detected no more than about 45 ° rotation of the human face, and from Facial Expression, scale and number of impact, and lower error rate. Platform: |
Size: 191488 |
Author:lll |
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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: 在广泛研究前人工作的基础上，本文对运动人物的检测、跟踪与识别进行了综述。为
使分类清楚明了，本文将人物运动分析分为两大类：人体运动分析，人脸分析。人体运动分
析包括人的较大幅度的肢体运动，如手势识别、步态分析、整个人体的运动分析；人脸分析
包括人脸检测与识别、表情分析。在详细介绍了国内外研究现状后，提出了存在的问题及研
究前景。-Extensively studied in previous work on the basis of the figures in this article on the movement detection, tracking and recognition are reviewed. To enable a clear understanding of classification, motion analysis of figures in this article will be divided into two categories: human motion analysis, analysis of human faces. Analysis of human motion including the relatively large body movements, such as gesture recognition, gait analysis, motion analysis of the human body Facial analysis includes face detection and recognition, facial expression analysis. In the study described in detail the status quo at home and abroad, the proposed study of the problems and prospects. Platform: |
Size: 357376 |
Author:martin |
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Description: 基于弹性模板匹配的人脸表情识别程序。首先针对静态表情图像进行表情图像的灰度、尺寸归一化，然后利用Gabor小波变换提取人脸表情特征以构造表情弹性图，最后提出基于弹性模板匹配及K-近邻的分类算法实现人脸表情的识别。-Flexible template matching based on facial expression recognition procedures. First of all, the expression for the static image of the gray-scale face image, size, normalized, and then extracted using Gabor wavelet transform features of human facial expression to expression of elastic graph structure, and finally based on flexible template matching and the K-neighbors classification algorithm Facial Expression identification. Platform: |
Size: 763904 |
Author:hejian |
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Description: 很流行的一种人脸面部表情特征提取方法
C++代码-Very popular expression of a human face feature extraction method of the Department of C++ code Platform: |
Size: 6144 |
Author:annie |
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Description: 摘 要： 提出了一种基于改进 Ha u s d o r f f距离的人脸相似度匹配的方法， 该方法首先将人脸划分为脸型、 双眼、 鼻、 嘴等几个特征点
集， 分别计算各部分的改进 Ha u s d o r f f 距离， 然后进行加权计算相似度。利用该方法， 在 A S M( 主动形状模型) 定位人脸的基础上进
行了人脸检索。 实验表明， 利用人脸相似度计算方法对人脸特征库进行搜索， 达到 了较好的效果。同时结合 A S M 自动人脸检测， 本
方法可以全自动完成人脸匹配， 应用于人脸识别及数字娱乐等领域。-Abstract: This paper presents a distance based on an improved Ha usdorff face similarity matching method, which will first face is divided into face, eyes, nose, mouth, and several other feature point sets, were calculated to improve the various parts of Ha usdorff distance, and then weighted similarity. Using this method, in the ASM (active shape model) positioned on the basis of human face human face retrieval. Experiments show that the use of face similarity calculation method for facial feature database to search, to achieve good results. ASM automatically combined with face detection, this method can be completed fully automatic human face matching, used in face recognition and digital entertainment and other fields. Platform: |
Size: 202752 |
Author:alsocc |
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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: 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: 三维游戏动漫人物设计中人脸核心表情库的构建-Three-dimensional game design cartoon characters face the core of human expression library construction Platform: |
Size: 2783232 |
Author:胡强 |
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Description: 在广泛研究前人工作的基础上，本文对运动人物的检测、跟踪与识别进行了综述。为使分类清楚明了，本文将人物运动分析分为两大类：人体运动分析，人脸分析。人体运动分析包括括人的较大幅度的肢体运动，如手势识别、步态分析、整个人体的运动分析；人脸分析包括人脸检测与识别、表情分析。在详细介绍了国内外研究现状后，提出了存在的问题及研究前景。
-On the basis of previous work in the extensive research, detection, tracking and recognition of moving figures were reviewed. Clear classification, character movement analysis is divided into two major categories: human motion analysis, face. Human motion analysis including including more substantial limb movements, such as gesture recognition, gait analysis, motion analysis of the entire human body human face analysis including face detection and recognition, expression analysis. Detailed research status, Problems and research prospects. Platform: |
Size: 357376 |
Author:kommkk |
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Description: 首先利用人脸的色彩特征和自适应阈值法实现特征候选区域和人脸肤色区域的分离，然后利用人脸的几何特性将连通的特征候选
区域保留下来作为人脸特征区域。后续的特征提取可以在这些人脸特征区域中完成。一般的人脸特征提取方法都可以将该方法作为提高效
率的预处理操作。实验证明，该方法具有高效率、低计算量的特点，并且受人脸表情、图像角度和背景的影响较小。-First, the use of the color characteristics of the human face and adaptive thresholding feature candidate region and the skin color of the face area of separation, then the use of the geometric characteristics of the face to the connectivity features of candidate regions preserved as a facial feature region. Subsequent feature extraction can be completed in the area of these facial feature. General facial feature extraction methods the method as a pre-processing operations to improve efficiency. The experiments show that this method has the characteristics of high efficiency, low computational smaller, and the facial expression, the image angle and background. Platform: |
Size: 108544 |
Author:东方 |
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Description: 基于稀疏表达的包含测试和训练人脸的数据库的鲁棒性人脸识别-Sparse expression includes testing and training human face recognition database robustness Platform: |
Size: 3876864 |
Author:CC |
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Description: 这个是LBP人脸算法，对学习者有很好的帮助，关于人脸表情识别，这里是基于ORL人脸库。-This is the human face LBP algorithm, the learners have good help, on facial expression recognition, here is based on the ORL database. Platform: |
Size: 3635200 |
Author:chen |
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Description: Face is a primary focus of attention in social intercourse, playing a major role in conveying identity and
emotion. The human ability to recognize faces is remarkable. People can recognize thousands of faces learned throughout
their lifetime and identify familiar faces at a glance even after years of separation. This skill is quite robust, despite large
changes in the visual stimulus due to viewing conditions, expression, aging, and distractions such as glasses, beards or
changes in hair style. In this work, a system is designed to recognize human faces depending on their facial features. Also
to reveal the outline of the face, eyes and nose, edge detection technique has been used. Facial features are extracted in the
form of distance between important feature points. After normalization, these feature vectors are learned by artificial
neural network and used to recognize facial image. Platform: |
Size: 240640 |
Author:fatemeh |
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Description: 1. 使用matlab自带的人脸识别工具（Viola-Jones算法）找出人脸的位置，并裁剪出人脸区域。
2. 使用Gabor滤波器识别出人脸的局部特征及纹理。
3. 训练一个SVM进行表情分类。
4. 交叉验证得到表情分类正确率为83.3 。
操作说明和系统描述请见ReadMe.-1. Using matlab with face detection tool (Viola-Jones algorithm) to find the location of a human face, and cut out the face region.
2. Use Gabor filter to identify the face local feature and texture.
3. Adopt SVM to train a facial expression classifier.
4. Use cross-validation to exam the classification accuracy: 83.3 . Platform: |
Size: 5593088 |
Author:冯溢 |
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Description: 使用OPENCV库提供的接口，实现人脸的识别功能。
在一个人脸识别系统中，应用多种预处理技术对将要识别的图片进行标准化处理是极其重要的。多数人脸识别算法对光照条件十分敏感，所以假如在暗室训练，在明亮的房间就可能不会被识别出来等等。比如脸部也应当在图片的一个十分固定的位置（比如眼睛位置为相同的像素坐标），固定的大小，旋转角度，头发和装饰，表情（笑，怒等），光照方向（向左或向上等），这就是在进行人脸识别前，使用好的图片预处理过滤器十分重要的原因。你还应该做一些其它事情，比如去除脸部周围的多余像素（如用椭圆遮罩，只显示其内部的人脸区域而不是头发或图片背景，因为他们的变化多于脸部区域）。(Using the interface provided by the OPENCV library, the face recognition function is realized.
In a human face recognition system, it is very important to use a variety of preprocessing techniques to standardize the pictures to be recognized. Most face recognition algorithms are very sensitive to light conditions, so if they are trained in a dark room, they may not be recognized in a bright room. Such as the face should also be in a picture is a fixed position (such as eye position for the same pixel coordinates), fixed size, rotation angle, hair and decoration, expression (laughter, anger), light direction (left or upward), which is in face recognition, the use of good the image preprocessing filter very important reason. You should also do some other things, such as the removal of redundant pixels around the face (such as elliptical mask, showing only the face region rather than the internal hair or picture background, because they change more than the face area).) Platform: |
Size: 68291584 |
Author:小女百合
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Search - human face expression