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EAR
- 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
src
- 用神经网络来进行人脸识别的程序,对脸部的表情进行识别,如高兴,伤心等-Using neural networks for face recognition program, to identify facial expressions such as happy, sad, etc.
贝叶斯实现人脸表情的识别
- 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
work
- 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
STLBP_VC
- 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,"
An-Algorithm-for-face-Recognition-
- 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。-
net
- 用c写的BP神经网络人脸识别,可以识别姿势,表情,是否带太阳镜。gcc下执行通过,其中含有说明文件,注意编译和执行时放好文件夹的路径-C write with the BP neural network face recognition, can recognize gestures, facial expressions, whether with sunglasses. performed by gcc, which contains documentation, pay attention
manu
- A method for extracting information about facial expressions from images is presented. Facial expression images are coded using a multi-orientation, multi-resolution set of Gabor filters which are topographically ordered and aligned approxima
untitled
- A database of facial expression images was collected. Ten expressors posed 3 or 4 examples of each of the six basic facial expressions (happiness, sadness, surprise, anger, disgust, fear) [4] and a neutral face for a total of 219 images of fa