搜索资源列表
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.
ch2_ex2_8
- 用于图像追踪的算法,比传统算法准确度更高,并且速度更快。-or image tracking algorithm than traditional algorithm accuracy, and faster.
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.
face_detect
- 使用opencv实现人脸检测功能,检测率高、速度快,编译本程序前需要预先安装好opencv库-Opencv face detection function, high detection rate and speed required to compile the program pre-installed opencv library
ImageStitch
- 基于垂直投影的图像水平拼接 这种算法匹配特征少,速度快-Open cv.
OnlinePCA
- 通过在线PCA来识别手势,并能对新增手势做一定的增量,很好的实现了增量学习。算法具有效率高,识别率好,速度快等特点,同样适合其他模式识别方面的应用。-The learning method for hand gesture recognition system based on vision is commonly off-line,which results in repeated off-line learning when new hand gestures come. Its real-
SIFT-feature-matching-
- SIFT 特征匹配算法是目前国内外特征点匹配研究领域的热点与难点,其匹配能力较强,可以处 理两幅图像之间发生平移、旋转、仿射变换情况下的匹配问题,甚至在某种程度上对任意角度拍摄 的图像也具备较为稳定的特征匹配能力。该算法目前外文资料较多,但中文方面的介绍较少。为此 我撰写了这篇文档,以帮助国内的研究学者尽快入门,以最快的速度去体验 特征匹配算法是目前国内外特征点匹配研究领域的热点与难点,其匹配能力较强,可以处 理两幅图像之间发生平移、旋转、仿射变换情况下的匹配问题,甚至在某种
OpenCV-Face-detection
- 程序中提供了一种简单方便的人脸面部特征提取方法,测方法提取人脸特征效率高,速度快,提取精度高-The program provides a simple and convenient method for human facial feature extraction, measurement methods to extract facial features high efficiency, high speed, high precision extraction
OpenCv--based-image-retrieval-DEMO
- 基于OpenCv开发的图像检索DEMO,速度较快,效果较好,可以作为一般意义下的图像相似度检索服务!根据具体项目改改即可使用!-OpenCv developed based image retrieval DEMO, faster, better, can be used as image similarity retrieval services in a generic sense! Changed to use the specific project!
Vibe
- ViBe运动检测,特点是建模速度快,在第一帧便完成了场景建模,缺点是容易产生ghost,需要安装opencv环境。-ViBe : motion detection
display-vedio
- 利用opencv源代码显示视频图像,代码简单运行速度快-display vedio
IMAGE-MOVE-BASED-ON-OPENCV
- 基于OPENCV的图像平移方法:利用鼠标标左键的响应移动图像,速度快。-Image moving method based on OPENCV:using the left mouse to move the image with fast speed
Background-difference-method
- 背景差分法是采用图像序列中的当前帧和背景参考模型比较来检测运动物体的一种方法,其性能依赖于所使用的背景建模技术。背景差分法检测运动目标速度快,检测准确,易于实现,其关键是背景图像的获取。在实际应用中,静止背景是不易直接获得的,同时,由于背景图像的动态变化,需要通过视频序列的帧间信息来估计和恢复背景,即背景重建,所以要选择性的更新背景。-Background difference method is the use of images in the sequence of the current
zbar-master
- 基于java编写的zbar二维码识别库。亲测可用。识别速度快,准确率较高(ZBar QR code recognition library based on Java. Pro test available. High recognition speed and accuracy)