Stereo1

说明：  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.)

说明：  采用考虑湍流内外尺度影响的退化模型来恢复大气湍流降质图像，运用包含了湍流内外尺度影响的波结构函数、折射率谱以及薄透镜成像的退化函数导出了新的退化模型。(A new degradation model includling the influence of outer-and inner-scale of turbulence is presented to restore atmospheric turbulence degradation images. )

圆形图表的处理，包括大圆套小圆，双指针，针对设计仪表的初学者很有帮助(Treatment of circular charts, including the great circle sets of small round, double pointer, very helpful for beginners instrument design)

说明：  包括pca和lda两个文件，先用pca降维后进行lda进行分类，用于人脸识别，实验结果很好。(It includes 2 files pca and lda. After the dimensionality reduction of pca, use lda for classification in face recognition. It has a very good experimental results.)

一种针对光照不均且低对比度环境下的水下图像增强算法。(Underwater image enhancement algorithm in a low contrast environment)

cvpr2012_oral On Multiple Foreground Cosegmentation(In this paper, we address a challenging image segmentation problem called multiple foreground cosegmentation (MFC), which concerns a realistic scenario in general Webuser photo sets where a finite number of K foregrounds of interest repeatedly occur over the entire photo set, but only an unknown subset of them is presented in each image. This contrasts the classical cosegmentation problem dealt with by most existing algorithms, which assume a much simpler but less realistic setting where the same set of foregrounds recurs in every image. We propose a novel optimization method for MFC, which makes no assumption on foreground configurations and does not suffer from the aforementioned limitation, while still leverages all the benefits of having co-occurring or (partially) recurring contents across images. Our method builds on an iterative scheme that alternates between a foreground modeling module and a region assignment module, both highly efficient and scalable. In part)

Freeman链码（8方向）代码，进行图像边缘的描述，可用于基于内容的图像检索系统(Freeman chain code (8 directions) code)

介绍CEGUI中所给的例子的的文档，很详细.(Introduce the samples in the CECUI,very detailed!)

说明：  模糊C均值聚类算法的MATLAB实现，比较经典的程序(Fuzzy C-means clustering algorithm to achieve MATLAB, compare the classic procedure)

动目标检测，包括动目标检测理论，动目标检测器，目标检测公式(Moving target detection, including moving target detection theory, moving object detection, object detection formula)