指纹识别相关代码 希望大家有用 edgedetect.cpp edgedetect.h fmt_bitmap.cpp fmt_bitmap.h...

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.

摄像头标定，我最近在做摄像头标定，这个程序需要一张标定纸，我用的是7×7-Camera calibration, I recently make camera calibration, the calibration process requires a paper, I use the 7 × 7

c内嵌汇编的一个示例-a compilation of examples

一篇关于行人检测的文件 经典大家可以看看 学习下-Pedestrian Detection on a document everyone can look at the classic study of

在屏幕上选取点集，每四个点构成一个控制多边形，绘制贝塞尔曲线和赫米特曲线-Select the point on the screen sets, each of the four points form a control polygon, drawing Bezier curves and hermite curve

一个类似coredraw中可以通过拉动矩形筐，来动态改变图元大小的源代码，vc编的。-CoreDraw in a similar rectangular basket by pulling, to dynamically change the pixel size of the source code, vc series.

硬件加速的绘制排序算法HAVS。可用在大规模数据的可视化中。-Hardware-accelerated rendering sorting algorithm HAVS. Can be used in large-scale data visualization.

基于GVF的SNAKE一个实现的重要函数GVFC，网上搜得-An important function GVFC used to implement the snake (active contour) based on the GVF (gradient vector flow).

用两个窗口实现三维物体显示的源程序，编程环境为.net2003和d3d。-Realize two windows with three-dimensional objects displayed on the source code, programming environment. Net2003 and d3d.

使用Kalman滤波器跟踪一个旋转的点，用于特征点的跟踪-Use Kalman filter to track a rotating point for the tracking of feature points