搜索资源列表
SLLE
- 稀疏流形建模及其在人脸识别中的应用论文介绍稀疏理论 以及sparse LLE -Sparse manifold modeling and its application to face recognition paper introduces the theory and sparse LLE sparse
SRC 实现了使用基于稀疏表示的人脸识别算法
- 该源码实现了使用基于稀疏表示的人脸识别算法。使用GPSR作为l1模最小化方法。-This pack of code implement a imges-based face recognition using sparse representation classification. In the algorithm, i employ GPSR as tool to complete the optimization procedure of l1-minimization.
FaceRecogTool
- 基于稀疏表示的人脸识别系统，用matlab GUI写出，运行成功-Based on sparse said face recognition system with matlab GUI write, operation success
l1_ls_nonneg
- 用于稀疏表示求解L1稀疏系数，特点是本程序是用于求解非负的稀疏系数-this procedure is used to solve the sparse non-negative coefficient
RSC
- 强壮的人脸识别系统，发表于cvpr2011年，程序是应用matlab实现-Recently the sparse representation (or coding) based classifi cation (SRC) has been successfully used in face recognition. In SRC, the testing image is represented as a sparse linear combination of the trai
bundler-v0.3-source.tar
- Bundler is a structure-from-motion system for unordered image collections (for instance, images from the Internet). Bundler takes a set of images, image features, and image matches as input, and produces a 3D reconstruction of the camera and (s
Unsupervised_Learning_of_Human_Action_Categories.r
- 基于时空域稀疏性表征的人的行为识别和理解的算法研究的论文，采用了非监督学习的方法，具有很*价值。-When the airspace based on sparse representation of human behavior recognition and understanding of the algorithm research paper, using non-supervised learning method, has great reference value.
CVPR09-ScSPM
- 基于空间金字塔匹配的稀疏编码，用于图像检索和图像识别。-Spatial pyramid matching based on sparse coding for image retrieval and image recognition.
l2
- sparse recognition classification人脸识别。extend yaleB数据库10类-sparse recognition classification for face recognition. yaleB database
FACE-RECOGNITION
- 此文的目的有三个：第一，当地连续均值量化变换特征是提出照明和传感器敏感操作在目标识别上。其次，注册稀疏Winnows网络分割，提出了加快原分类。最后，特点和分类相结合对于正面人脸检测任务。检测结果列 为MIT + CMU系统和BioID数据库。关于这人脸检测器，接收器操作特征曲线BioID数据库产生最好的结果公布。对于结果麻省理工学院的中央结算系统+数据库相当于国家的最先进的脸探测器。一个人脸检测算法的MATLAB版本可以从http://www.mathworks.com/matlabce
Metaface_ICIP
- 利用稀疏表示一集字典学习的方法进行人脸自动识别的Matlab算法，是经典SRC方法的提高-That a sparse set of dictionary use of learning methods in Matlab automatic face recognition algorithms, is the classic method of improving SRC
RSC
- 人脸识别的稀疏表示识别方法将稀疏表示的保真度表示为余项的L2范数，但最大似然估计理论证明这样的假设要求余项服从高斯分布，实际中这样的分布可能并不成立，特别是当测试图像中存在噪声、遮挡和伪装等异常像素，这就导致传统的保真度表达式所构造的稀疏表示模型对上述这些情况缺少足够的鲁棒性。而最大似然稀疏表示识别模型则基于最大似然估计理论，将保真度表达式改写为余项的最大似然分布函数，并将最大似然问题转化为一个加权优化问题-Recently the sparse representation (or codin
Collaborative-Representation
- 稀疏表示和协同编码哪个对人脸识别起到了决定作用。在稀疏表示的人脸识别中，到底是因为稀疏表示的作用还是他们之间的协同编码起了作用。-Sparse Representation or Collaborative Representation: Which Helps Face Recognition ICCV2011
PRPSRPSTAT
- My collection of books and lectures on pattern recognition and sparse representation.
wulianwangchepaishibian
- 物联网环境下车牌识别的稀疏表示及其应用研究-Sparse representation of the license plate recognition under the environment of the Internet of Things and its application
chepaishibianshuoming-
- 车牌识别说明，有关物联网的车牌识别问题解析说明-Sparse representation of the license plate recognition under the environment of the Internet of Things and its application
orl_92x112
- 这是一个用于基于稀疏表示的人脸识别图形库-This is a face recognition based on sparse representation graphics library
sr
- 基于稀疏表示来实现图像的目标识别的几种算法-Image based on sparse representation to achieve the objectives identified several algorithms
Sparse-representation-
- 介绍几种算法来确定稀疏表示的稀疏系数的求解方法-Introduce several algorithms to determine the sparse representation method for solving sparse coefficient
RSC
- Robust sparse coding(RSC),对带遮挡的人脸识别有效，附带有l1范求解工具包-Robust sparse coding (RSC), effective for face recognition with occlusion l1 norm solving toolkit