视频异常检测 须安装jmf 参考论文 Robust Real

Revoluntion IDL示例程序 Revolution IDL unleashes the power of the IDL Object Graphics architecture by providing a high- level graphical user interface that allows the user to visualize data in a variety of ways, changing properties, positioning objects in 3D, and much more. -Example Revoluntion IDL procedures Revolution IDL unleashes the power of the IDL Object Graphics architecture by providing a high-level graphical user interface that allows the user to visualize data in a variety of ways, changing properties, positioning objects in 3D, and much more.

基于ORL人脸库的主元分析法用于人脸识别-ORL face database based on the principal component analysis method for face recognition

手写数字识别之Fisher线性判别-handwritten figures identifiable Fisher Linear Discriminant

长方形的填充和背景填充-rectangular background filled and filled

用VC++开发的图像压缩-development of the VC Image Compression

二维几何变换，包括图像的平移变换、切磋变换、缩放变换、旋转变换-Two-dimensional geometric transformations, including the image of the translation transformation, Qiecuo transform, scale transform, rotation transformation

采用镶嵌图的人脸检测程序，速度快，精度没有adaboost好，可以供学习使用-using mosaic of face detection procedures, speed and accuracy not adaboost good, can be used for learning

Abstract We present a component-based, trainable system for detecting frontal and near-frontal views of faces in still gray images. The system consists of a two-level hierarchy of Support Vector Machine (SVM) classifiers. On the first level, component classifiers independently detect components of a face. On the second level, a single classifier checks if the geometrical configuration of the detected components in the image matches a geometrical model of a face. We propose a method for automatically learning components by using 3-D head models. This approach has the advantage that no manual interaction is required for choosing and extracting components. Experiments show that the componentbased system is significantly more robust against rotations in depth than a comparable system trained on whole face patterns.

实现盲信号分离的独立成分分析的算法,用Informax实现-the arithmetic realize the ica

用vc + mapobjects开发的源代码，用鼠标对多边形进行操作，实现了多边形计算的功能。-with vc MapObjects development of the source code, using the mouse to operate polygons and achieve the polygon count function.