stereovision

这篇文章是一种特征降维的方法，不过跟一般的计较离散度的方法不同，这个特征变换的准则是：尽可能地保留原始样本的熵(Kernel Entropy Component Analysis Jenssen, R Pattern Analysis and Machine Intelligence, IEEE Transactions on Volume: PP , Issue: 99 )

gac模型的迎风方案可以实现对灰度图像的分割，分割效果还可以(gac)

说明：  联合特征选择和子空间相关性学习的跨模态检索，map优于典型相关性分析的跨模态检索(Joint Feature Selection and Subspace Learning for Cross-Modal Retrieval)

说明：  After spending a decade cooking in Michelin-starred restaurants in Spain, chef Oswaldo Oliva returns to his native Mexico City with a menu that rivals that of Pujol

说明：  图像处理，图像分割，图像变换，图像特征提取，图像增强，图像编码压缩(Image processing, image segmentation, image transformation, feature extraction)

idl 可视化分析与应用（随书程序），详细的程序与应用。(idl visualization analysis and application (with the book procedures), the detailed procedures and applications.)

说明：  读图然后根据图像的对象，进行边缘检测，椭圆拟合(Read the image and then carry out edge detection and ellipse fitting according to the object of the image)

说明：  基于C#的模糊雾化处理。 高斯雾化 C #-based processing of fuzzy atomization. Gaussian Atomization(C#-based processing of fuzzy atomization. Gaussian atomization C#-based processing of fuzzy atomization. Gaussian Atomization)

一种简单高效地基于压缩感知的跟踪算法。首先利用符合压缩感知RIP条件的随机感知矩对多尺度图像特征进行降维，然后在降维后的特征上采用简单的朴素贝叶斯分类器进行分类。该跟踪算法非常简单，但是实验结果很鲁棒，速度大概能到达40帧/秒(A simple and efficient tracking algorithm based on compressed sensing. Firstly, with the random sensing matrix compressed sensing RIP conditions for multi-scale image feature dimension reduction, and then use the naive Bias classifier simple classification in the feature reduction after the. The tracking algorithm is very simple, but the results are robust, speed can reach 40 frames per second)

运用harr特征+SRC（稀疏表示）分类实现的一种车辆检测方法，文件中提供了训练和测试车辆图片。由于时间原因，所用haar特征没有优化，维度过高，导致滑窗框图过慢，本代码只输出效果统计数据，以供大家参考学习稀疏表示在车辆检测中的应用。(Using harr feature+SRC (sparse representation) classification to achieve a vehicle detection method, the paper provides a training and test vehicle picture. Due to time reasons, the use of haar feature is not optimized, high dimension, resulting in sliding sash figure is too slow, the effect of the code only output statistics for your reference learning sparse representation in the vehicle detection.)