houghtoedge

说明：  利用BOW结合空间金字塔模型，使用支持向量机进行图像分类(Image classification using bow)

8通道GRAPPA并行重建算法，4倍加速(Parallel reconstruction algorithms ,GRAPPA，R=4)

使用Matlab实现LMS自适应滤波，实现的主要功能有：读入原始音频，加入高斯噪声后用LMS自适应滤波滤除，比较原始音频，加入噪声音频和滤波后音频的区别。(Matlab achieved using LMS adaptive filtering to achieve the main features are: read the original audio, adding Gaussian noise is filtered using LMS adaptive filtering, comparing the original audio, add audio and noise filtered audio difference.)

用Matlab实现的Canny边缘检测算法，压缩文件中附有一张实验图片(Using Matlab realize the Canny edge detection algorithm, compressed file attached to an experimental image)

这是一个实现了发表在CVPR2006的抠图算法。(This package contains an implementation of the matting algorithm described in the CVPR2006 paper.)

基于dft变换域的图像水印嵌入程序，通过修改分块dft系数实现水印嵌入，可实现，供初学者参考。(Dft transform domain image watermarking embedding the watermark embedding process by modifying the block dft coefficients, achievable, and reference for beginners.)

标定投影仪与摄像机之间的透视变换矩阵，将摄像机图像转换成投影仪视角下的图像(calibration and transformation between camera and projector)

SDK_key: 人脸追踪(FT) Key 5qTrdeA43zdBXJZt7HM1x1wX9XGt7QicRU6Nt8rXLQAn 人脸检测(FD) Key 5qTrdeA43zdBXJZt7HM1x1weJvY2koYyzGARH6wVoTVw 人脸识别(FR) Key 5qTrdeA43zdBXJZt7HM1x1wmUKoEpvhgJYHd5xAsFig3 年龄识别(Age) Key 5qTrdeA43zdBXJZt7HM1x1xPHL78Ekcog6LU5iNCCNLj 性别识别(Gender) Key 5qTrdeA43zdBXJZt7HM1x1xWSjNHHcbTHHP9VuHLX1rf 此处APP_Id与SDK_Key仅适用于ArcFace v1.1， 不适用于其他版本。(DK_key: Face Tracking (FT) Key 5qTrdeA43zdBXJZt7HM1x1wX9XGt7QicRU6Nt8rXLQAn Face Detection (FD) Key 5qTrdeA43zdBXJZt7HM1x1weJvY2koYzGARH6wVoTVw Face Recognition (FR) Key 5qTrdeA43zdBXJZt7HM1x1wmUKoEpvhg JYHd5xAsFig3 Age Identification (Age) Key 5qTrde A43zdBXJZt7HM1x1xPHL78Ekcog 6LU5iNCCNLj Gender Key 5qTrdeA43zdBXJZt7HM1x1xWSjNHcbTHHP9VuHLX1rf Here APP_Id and SDK_Key are only applicable to ArcFace v1.1, not to other versions.)

建立一个透明物体上有污点的模型，可以模拟玻璃上有污点的图象(Rendering of clean transparent objects has been well studied in computer graphics. However, real-world transparent objects are seldom clean—their surfaces have a variety of contaminants such as dust, dirt, and lipids. These contaminants produce a number of complex volumetric scattering effects that must be taken into account when creating photorealistic renderings. In this paper, we take a step toward modeling and rendering these effects. We make the assumption that the contaminant is an optically thin layer and construct an analytic model following results in radiative transport theory and computer graphics. Moreover, the spatial textures created by the different types of contamination are also important in achieving visual realism. To this end, we measure the spatially varying thicknesses and the scattering parameters of a number of glass panes with various types of dust, dirt, and lipids. We also develop a simple interactive synthesis tool to create novel instances of the me)

使用matlab搭建神经网络，从单目图像中估计深度值(Using matlab to build a neural network to estimate depth from monocular images)