搜索资源列表
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使用OPENCV实现基于隐马尔科夫过程人脸表情识别,OPENCV use of hidden Markov process based on Facial Expression Recognition
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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-sca
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很好的关于人脸识别的毕业论文，从中国知网付费下载得到，《基于嵌入式隐马尔可夫模型（EHMM）的人脸表情识别 》希望对大家有用。-About Face Recognition of good theses, pay-per-download from the Chinese HowNet be, " Based on Embedded Hidden Markov Model (EHMM) Facial Expression Recognition" I hope useful t
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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
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基于高波滤波的特征提取技术，从而实现人脸识别和表情识别的目的-Based on high-wave filter feature extraction techniques, in order to achieve the purpose of face recognition and expression recognition
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：针对传统Gabor变换在提取表情特征时，冗余较大、特征维数较高的不足，结合ASM
自动特征定位技术，提出了一种基于特征点Gabor特征和ASM 形状特征相融合的面部表情
识别方法．实验表明，两种特征的融合，可有效地利用特征点的局部纹理信息和脸部器官的整
体形状信息，达到了更好的面部表情识另4效果．-: Gabor transform traditional expression feature extraction, the redundancy large feature dim
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提出了基于特征融合和模糊核判别分析(FKDA)的面部表情识别方法。首先，从每幅人脸图像中手工定
位34个基准点，作为面部表情图像的几何特征，同时采用Gabor小波变换方法对每幅表情图像进行变换，并提取基
准点处的Gabor小波系数值作为表情图像的Gabor特征；其次，利用典型相关分析技术对几何特征和Gabor特征进
行特征融合，作为表情识别的输人特征；然后，利用模糊核判别分析方法进一步提取表情的鉴别特征；最后，采用最
近邻分类器完成表情的分类识别。通过在JAFFE国际表情数据库和
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supplies
cross-platform libraries for real-time perception primitives, including face detection,
eye detection, blink detection, color tracking. Soon it will also include expression
recognition, predictive color tracking, and tracking based on
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One of Biometrics fields is face recognition & face expression recognition ...
1- In face recognition .. we need to design authentication program by training a neural network ,there are two source codes..one of them is based on Discrete Wavelet Tr
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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 of face
images, it is of
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facilitate the user s task. One such approach is the
object-related image retrieval. In the context of face
images, it is of interest to retrieve images based on
people s names and facial expressions. However, when
images of the database a
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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 of face
images, it is of
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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 of face
images, it is of
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This paper investigates a new face recognition system based on an efficient design of classifier using SIFT (Scale
Invariant Feature Transform) feature keypoint. This proposed system takes the advantage of SIFT feature which possess strong
robust
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一种基于弹性模板匹配的人脸表情识别程序源码。首先针对静态表情图像进行表情图像的灰度、尺寸归一化，然后后运用Gabor小波变换提取人脸表情特征以构造表情弹性图，最后提出一种基于弹性模板匹配及K 可直接使用。
-Facial expression recognition based on elastic template matching program source code. First the face image of the gray-scale images for static e
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在目前的人脸图像信息处理领域中，包含有人脸识别、人脸跟踪、姿态估计、表情识别等多个研究方向，然而，所有这些研究方向都涉及到一个人脸标识和定位的问题，即必须知道人脸在图像中的位置以及尺寸——人脸检测。因此，对于一个完整的、自动的人脸信息分析系统来说，人脸检测算法是必不可少的。本文主要是对基于matlab平台的彩色图像皮肤区域分割算法及人脸检测系统的设计做了介绍。-In the face image information processing, including face recogniti
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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.
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这个是面部表情自动识别的源代码。它是基于Viola和Jones的面部检测算法和Gabor面部特征点的提取，然后使用训练过的神经网络来识别人脸表情。-This is the automatic recognition of facial expression source code. It is Viola and Jones face detection algorithms and Gabor facial feature point extraction, and then use the
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MATLAB编写的基于稀疏表达的人脸识别技术，内含一个简单便于理解的例子-MATLAB prepared based on face recognition technology sparse expression, there is a need to see! !
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人脸检测方法主要有基于知识的方法、特征不变方法、模板匹配方法、基于外观的方法；脸部特征定位方法分为基于先验知识、几何形状、色彩、外观和关联信息等五类；人脸表情识别方法分为基于几何特征的识别方法，基于整体的识别方法，基于模型的识别方法，基于模板的识别方法。-Face detection methods are mainly based on knowledge of the method, the characteristics of constant method, template match
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