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用meanshift方法在opencv和vs2008上实现运动物体的检测与跟踪。-Meanshift methods used to achieve the opencv and vs2008 moving object detection and tracking.
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ray-tracing光线跟踪算法的实现。包括了光线求交、追踪,物体材质、色彩的设置,球面和墙面的镜面反射效果。场景包括地板,三个镜面反射的球体,一个漫反射球体和一面镜面反射的墙壁。工程运行于VS2008环境,需要OpenGL支持。Release目下exe文件可以直接双击运行查看结果(需要glut32.dll动态链接库的支持)。-ray-tracing ray tracing algorithm. Includes light intersection, tracking, object mat
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This article describes the basics of working with images, motion analysis and tracking of the object in OpenCV.
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在视频中,用OpenCV工具,对运动物体进行跟踪,获取它的位置-Tracking of Object Using OpenCV
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是opencv的c++常用的所有的程序,包括人脸识别,运动物体跟踪,颜色识别,图形图像设计,摄像头定标等。-Is opencv c++ commonly used all programs, including face recognition, moving object tracking, color recognition, image design, camera calibration, etc.
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如果要跟踪的物体颜色和背景色有较大区别,可用基于颜色的跟踪 如CAMSHIFT 鲁棒性都是较好的。 此源码是一个opencv自带的CamShift算法使用工程实例(有非常详细的注释)。该实例的作用是跟踪摄像头中目标物体,目标物体初始位置用鼠标指出,其跟踪窗口大小和方向随着目标物体的变化而变化。-If you want to track the object color and background color is quite different, color-based tracking is
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基于Opencv的MeanShift跟踪代码。MeanShift算法是目标跟踪领域应用较广泛的算法,轻量级,原理是求概率密度最大位置。-Opencv based MeanShift tracking code. MeanShift is widely used in object tracking. lightweight. the principle is to find the probability density maximum position.
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Object tracking using opencv software with visual c++,this program tracks the object very fast & very accurately by varying threshold levels for particular object
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opencv学习,camshift,能实现物体跟踪,入门学习的简单例程-opencv learning, camshift, object tracking can be achieved, started to learn the simple routines
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结合kinect景深图像对视频目标进行跟踪,在vs2010+opencv平台上测试通过。-Combined with kinect depth of field image of the video object tracking on vs2010+ opencv test platform.
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OpenCV Object Detection and Tracking via SURF (Speeded Up Robust Features) in Emgu CV
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object tracking using opencv
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通过opencv实现彩色目标追踪,实现物体图像识别-Opencv track to achieve goals through color, to achieve the object image recognition
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This DSSIM program has been created by Philipp Klaus Krause based on
Rabah Mehdi's C++ implementation of SSIM (http://mehdi.rabah.free.fr/SSIM).
Originally it has been created for the VMV '09 paper
"ftc - floating precision texture compressio
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擴增實境技術是在真實視訊影像中加入虛擬物件,並透過追蹤與定位技術,可以與人們產生良好之互動效果。在視覺追蹤應用領域裡,可分為標記與無標記兩類應用。標記識別技術較為成熟,目前擴增實境開發平台以採用標記識別為主;至於無標記則侷限在特定方法之識別追蹤應用領域,例如樂高玩具利用包裝盒上之印刷圖片當作辨識物件。面對無標記擴增實境之應用日趨重要,且必須因應不同物件採用不同特徵之識別追蹤方法來達成無標記擴增實境之應用。而目前擴增實境平台並不提供模組化方式來替換識別追蹤方法,因此本文提出無標記擴增實境實驗平台,
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OpenCV的模式识别,图像处理,与运动物体跟踪编程-
OpenCV pattern recognition, image processing, and moving object tracking program
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基于LK光流法的目标跟踪,使用opencv开发-LK optical flow based object tracking using opencv development
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opencv下实现基于均值漂移的追踪技术,运行程序是,用鼠标框选择一个有颜色的物体,可以对它进行追踪操作-Opencv under the mean shift based tracking technology, running the program is to use the mouse to a color object, you can track the operation
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静态背景下运动物体跟踪,采用L-K光流法,opencv源代码-Moving object tracking in static background, using L-K optical flow method, opencv source code
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实现C++的KCF目标追踪算法,需要opencv平台的支持!(KCF object tracking)
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