搜索资源列表
face
- 基于高斯肤色模型的人脸检测技术，应用于人脸识别系统-face recognization based on gauss model
Face-Match
- 人脸检测系统， 通过人脸皮肤颜色模型， 识别人的脸部形状和特征-Face detection system, identify the person' s face shape and features of the face skin color model,
Color-face-recognition
- 实现基于肤色模型的人脸检测算法，包括基于相似度和几何特征以的非线性变换技术的算法的实现-Face detection algorithm based on skin color model, the realization of the algorithm based on similarity and geometric characteristics to non-linear transformation technology
Face-RecognitionMATLAB-CODE
- 在YCbCr色彩空间中建立肤色分布的高斯模型,得到肤色概率似然图像,在最佳动态阈值选取算法下完成肤色区域的分割。-YCbCr color space to establish the color distribution of the Gaussian model, color probability likelihood image, skin color region segmentation is completed in the best dynamic threshold select
PCA-Face-detection-and-recognition
- PCA 人脸检测识别 内容：人脸特征值提取 人脸模型重建，识别人脸-PCA face detection and recognition: facial feature value extraction， facial model reconstruction, recognize faces
face
- 这是一段自己编写的基于高斯模型的matlab人脸识别代码-This is a piece I have written matlab face recognition code based on the Gaussian model
Face-detection-based-on-skin-color
- 人脸检测，能够检测出多张人脸，通过建立肤色模型，图像预处理等，分割出肤色区域，效果不错。-Face detection and can detect more than one face, through the establishment of skin color model, image preprocessing, segmentation of color of skin area, the effect is good.
face-detection
- 基于肤色的人脸检测代码，建有肤色模型，有兴趣的可以下载下来-Face detection code based on skin color, skin color model, are interested can download them to see
generic-face-matlab
- candide-3 model face plotting
Face-orientation-recognition
- 本课题研究的步骤如下：先提取人脸的特征向量；产生训练样本和测试样本；再用LVQ创建神经网络模型，该模型用训练样本进行训练调整权值；用测试样本对建立的人脸朝向识别模型进行验证，要求有较高的识别率。 本课题要求使用LVQ神经网络的算法进行Matlab仿真，对人脸朝向进行有效的判断和识别。 -This study is the following steps: first extract facial feature vector generate training and testing
Face-orientation-recognition
- LVQ即学习向量量化神经网络是一种用于训练竞争层的有监督学习方法神经网络，在模式识别和优化领域有着广泛的应用。本课题要求使用LVQ神经网络训练人脸的特征数据，得到模型对任一人脸图像的朝向进行识别。-Learning Vector Quantization LVQ neural network that is used to train competitive layer neural network supervised learning methods in the field of patt
Model-Based-on-Perturbation-Theory
- 一种基于摄动理论的海底混响模型，详细分析了粗燥面条件下掠射角对海底混响模型的影响。-A shallow-water reverberation model is developed based on Bass perturbation theory. The key component for shallow-water reverberation modeling, the modal backscattering matrix (MBSM), has been investiga
Human-face-detection
- This file contains Human face detection based on skin color and model gaussian
model-CANDIDE
- 在模型与人脸初步匹配后, 对模型局部进行网格优化,提高了模型的表征力同时并不影响匹配速度 -In the initial model and face after the match, the model for local mesh optimization to improve the characterization of the model at the same time does not affect the matching speed force
face-recognise
- 针对不同的姿态对人脸识别的影响,提出了一个基于Candide-3参数模型的特 定人脸三维重建方法 -For different attitude on the impact of face recognition is proposed a parametric model based on Candide-3 specific 3D face reconstruction method
face
- 人脸识别程序，，建立肤色模型与pca等来进行对人脸图像识别-Recognition program, and so on pca skin model for image recognition of human faces
PCA_rec_FRGC_depth
- 運用PCA將高精度人臉的深度資料(FRGC database)分析主成分後重建低精度的Kinect深度資訊值，細化Kinect所產生的量測誤差。重建出較好的三維人臉模型-The depth of data using PCA face of precision (FRGC database) Principal component analysis of the reconstruction after the low accuracy of Kinect depth information v
face-recognition
- 基于神经网络的自动人脸识别模型，研究利用神经网络进行人脸识别的性能，通过与其它分类算法比较，为将来更进一步的人脸识别算法研究或者软件设计提供设计依据。-Automatic face recognition based on neural network model to study the use of neural network recognition performance, by comparison with other classification algorithms, provi
Edit68CMU_pack_AAM
- 基于 AAM 的人脸特征定位方法在建立人脸模型过程中，不但考虑 局部特征信息，而且综合考虑到全局形状和纹理信息，通过对人脸形状特征和纹 理特征进行统计分析，建立人脸混合模型，即为最终对应的 AAM 模型。-AAM facial features localization method based on face model in establishing the process, not only consider local feature information, and consi
Face_Recognition
- 基于opencv库中的人脸识别代码，可以实现检测并跟踪视频中的人脸，可以选择训练人脸模型，或者直接加载训练好的人脸模型来识别视频中的人脸身份。-Based opencv library, this face recognition code can be achieve detecting and tracking faces in the video. You can choose training face model, or load directly trained human face