搜索资源列表
tld1.0_demo
- 捕食者算法，快速精准定位，很好很强大，推荐下载，需要先安装MCR和matlab-Predators algorithm, fast precise positioning, very, very powerful, recommend download, need to install the MCR and matlab
optical-flow
- 光流算法，速度快，精度高，远远比OPENCV实现的要好。-Optical flow algorithm, fast, high accuracy, far better than OPENCV achieved.
fast_opencv(1.0)
- fast算法源代码，基于opencv下实现的源代码-fast algorithm source code, based on the source code to achieve opencv
SIFT_VC
- 非常快速高效的SIFT特征检测与匹配算法，用C++与OpecCV实现-SIFT features are very fast and efficient detection and matching algorithms, using C++ implementation with OpecCV
area-based-matching
- 一种快速的基于区域的立体匹配算法，英文论文，希望对你有用-A fast region-based stereo matching algorithm, the English papers, you want to be useful
cppbgfg_gaussmix2
- 背景建模方法之高斯混合模型，使用到MOG2。算法快，并且可以进行阴影检测。遍历性：对每一个像素进行建模。作者为Z.Zivkovic-The algorithm similar to the standard Stauffer&Grimson algorithm with additional selection of the number of the Gaussian components based on: "Recursive unsupervised learning of fini
BRIEF_demo-0.5
- BRIEF算法的DEMO，来自原作者，依赖OpenCV，速度非常快。-BRIEF algorithm of the DEMO, from the original author, dependent on OpenCV, very fast.
Classic-difference-algorithm
- 基于OPENCV的经典的差分算法，有快速，准确的特点-Classic difference algorithm based on OPENCV, fast, accurate features
agast_1_1
- AGAST算法，比FAST和FASTER更快-AGAST algorithm, which is faster than FAST and FASTER
TargeTraceing
- 采用 CAMSHIFT 算法快速跟踪和检测运动目标的 C/C++ 源代码，-Using CAMSHIFT algorithm for fast tracking and detection of moving targets in C/C++ source code,
OpencvCircle_Line
- Qt、Opencv环境下，演示ptr、at（）函数遍历图像示例，在该示例中显示了简单圆和线的绘制。仅仅用于教学演示，没有采用Bresenham等快速算法。-Under Qt, Opencv environment, demonstrate ptr, at () function to traverse a sample image showing the draw simple circles and lines in this example. Only for teaching demons
BoxFilter
- 自己编写的c代码，实现图像的快速均值滤波，采用盒子积分算法。-C write your own code, to achieve fast average filtering of the image, using box integration algorithm.
orb-recognition
- ORB算法是在FAST关键点检测+BRIEF特征上做的，是比较流行的一种匹配，克服了BRIEF的一些缺点！-ORB algorithm is the key point in the FAST feature detection+BRIEF do, it is more popular as a match, to overcome some of the shortcomings BRIEF!
KMkeen
- 基于人类视觉将图像分割成若干个有意义的区域是目标检测和模式识别的基础。图像分割属于图像处理中一种重要的图像分析技术。图像分割的基本方法是对灰度图像分割，处理图像的亮度分量，简单快速。本论文介绍了传统的图像分割与K-均值聚类算法分割，然后利用OpenCV函数将其实现，并介绍了OpenCV中图像分割相关的基本函数。-Based on the human visual image is segmented into several meaningful regions is the basis for
Fast-O(1)Bilateral-Filter
- Fast O(1)双边滤波算法,由三角函数逼近方法实现非迭代算法，计算量不再受滤波窗口大小影响，只与图像大小有关，适合改进为GPU执行的并行算法（此函数还包含一个递归高斯算法）-Fast O (1) bilateral filtering algorithm, approximation by a trigonometric method to achieve non-iterative algorithm to calculate the amount of the filter window
478487
- 从含有汽车的图像中找出彩色的车牌并且定位的快速算法(Find color from the image containing the car license plate and positioning of the fast algorithm)
quickly match
- 基于亮度/色彩一致性，在SURF算法的基础上提出了一种快速图像特征点匹配算法，可以缩小特征点匹配所需的运行时间，提高正确匹配率。(Based on the brightness / color consistency, a fast image feature point matching algorithm based on SURF algorithm is proposed, which can reduce the running time of feature point matchi