Description: Color-based tracking (CAMSHIFT) demo.
Alexandre R.J. Francois
Copyright (C) 2004 University of Southern California
介绍：CamShift是一种应用颜色信息的跟踪算法,在跟踪过程中,CamShift利用目标的颜色直方图模型得到每帧图像的颜色投影图,并根据上一帧跟踪的结果自适应调整搜索窗口的位置和大小,从而得到当前图像中目标的尺寸和中心位置.在该代码的框架基础上可以开发视屏游戏。-Color-based tracking (CAMSHIFT) demo. Alexandre RJ FrancoisCopyright (C) 2004 University of Southern California, introduced: CamShift is an application of color information of the tracking algorithm in the tracking process, CamShift use of the target color histogram model of each frame image color projection, and a track based on the results of adaptive search window location and size, resulting in the current target image size and central location. In the framework of the code can be developed based on the game screen. Platform: |
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Author:Andy |
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Description: A new approach toward target representation and localization, the central component in visual tracking
of non-rigid objects, is proposed. The feature histogram based target representations are regularized
by spatial masking with an isotropic kernel. The masking induces spatially-smooth similarity functions
suitable for gradient-based optimization, hence, the target localization problem can be formulated using
the basin of attraction of the local maxima. We employ a metric derived from the Bhattacharyya
coefficient as similarity measure, and use the mean shift procedure to perform the optimization. In the
presented tracking examples the new method successfully coped with camera motion, partial occlusions,
clutter, and target scale variations. Integration with motion filters and data association techniques is also
discussed. We describe only few of the potential applications: exploitation of background information,
Kalman tracking using motion models, and face tracking.-A new approach toward target representation and localization, the central component in visual trackingof non-rigid objects, is proposed. The feature histogram based target representations are regularizedby spatial masking with an isotropic kernel. The masking induces spatially-smooth similarity functionssuitable for gradient-based optimization, hence, the target localization problem can be formulated usingthe basin of attraction of the local maxima. We employ a metric derived from the Bhattacharyyacoefficient as similarity measure, and use the mean shift procedure to perform the optimization. In thepresented tracking examples the new method successfully coped with camera motion, partial occlusions, clutter, and target scale variations. Integration with motion filters and data association techniques is alsodiscussed. We describe only few of the potential applications: exploitation of background information, Kalman tracking using motion models, and face tracking . Platform: |
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Author: |
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Description: 基于Mean Shift算法和Particle Filter算法的目标跟踪学位论文：讨论了MeanS hift算法(均值偏移)和粒子滤波算法(Particle Filter)，分析了两种算法的特点；，分析了用运动目标检测提取目标运动特征的技术，通过增加对目标特征描述信
息，提高跟踪健壮性，并在以颜色直方图描述颜色特征的基础上，融合了目标的运动特征，设计了一种基于运动特征和颜色特征多特征融合的粒子滤波跟踪方法；用二阶直方图描述颜色特征，设计了均值偏移和粒子滤波相结合的目标跟踪技术-Based on Mean Shift Algorithm and Particle Filter algorithm for target tracking dissertation: The MeanS hift algorithm (average deviation) and particle filter (Particle Filter), an analysis of the characteristics of two algorithms analyzed by extracting the target moving target detection Movement characteristics of technology, by increasing the characterization of target information to enhance the tracking robustness, and to describe the color characteristics of color histogram, based on the integration of the target movement characteristics, designed a campaign based on the characteristics and color characteristics of multi-feature integration of particle filter tracking method with second-order description of the color histogram features, designed to offset the mean particle filter and a combination of target tracking technology Platform: |
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Author:田卉 |
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Description: 提出一种新的目标表示和定位方法,该方法是非刚体跟踪的核心技术.利用均质空间掩膜规范基于特征直方图的目标表示,该掩膜引入了适合于梯度优化的空间平滑相似函数,所以可以将目标定位问题转换为局部极大值求解问题.我们利用从Bhattacharyya系数倒出的规则作为相似度量,利用mean shift procedure完成优化求解.在给出的测试用例中, 本文方法成功解决了相机移动,阴影,以及其他的图象噪声干扰.文章对运动滤波和数据关联技术的集成也进行了讨论.-A new objective and positioning method to track non-rigid body' s core technology. Standardizing the use of homogeneous space mask the characteristics of histogram based on the objectives that the mask is suitable for the introduction of gradient optimization is similar to spatial smoothing function, Therefore, targeting the problem can be converted to solve the problem of local maxima. We poured from the rules of Bhattacharyya coefficient as similarity measure, using mean shift procedure for solving optimization. give the test cases in, the method succeeded in solving the camera Mobile, shadows, and other image noise. article on the campaign filtering and data association techniques of integration were also discussed. Platform: |
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Author:maolei |
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Description: A new approach toward target representation and localization, the central component in visual tracking of nonrigid objects,
is proposed. The feature histogram-based target representations are regularized by spatial masking with an isotropic kernel. The
masking induces spatially-smooth similarity functions suitable for gradient-based optimization, hence, the target localization problem
can be formulated using the basin of attraction of the local maxima. We employ a metric derived from the Bhattacharyya coefficient as
similarity measure, and use the mean shift procedure to perform the optimization. In the presented tracking examples, the new method
successfully coped with camera motion, partial occlusions, clutter, and target scale variations. Integration with motion filters and data
association techniques is also discussed. We describe only a few of the potential applications: exploitation of background information,
Kalman tracking using motion models, and face tracking. Platform: |
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Author:Ali |
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Description: 眨眼检测，先用haar特征框定人脸，然后用camshift跟踪人脸，根据几何特征得到人眼的大概位置，然后根据直方图的变化检测眨眼-Blink detection, the first feature with the haar framed face, and then use camshift tracking human face, according to the geometric features are the approximate location of the human eye, and then change detection histogram blink of an eye Platform: |
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Author:阿强 |
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Description: A new concept of tracking ball has been applied of detecting the ball in one frame by finding centroid ball ,finding histogram of the ball region and correlating it with candidate s histogram (by scanning the complete image) in subsequent frames. Matching of histogram indicates presence of ball ,hence tracks it. Platform: |
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Author:Vishwanath |
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Description: 一种基于纹理的Mean Shift目标跟踪算法Matlab源代码,论文<Robust Object Tracking using Joint Color-Texture Histogram>发表在2009年的International Journal of Pattern Recognition and Artifical Intelligence.-Matlab Code for An Texture based Mean Shift Tracking Algroithm. The paper <Robust Object Tracking using Joint Color-Texture Histogram> is published in International Journal of Pattern Recognition and Artifical Intelligence. Platform: |
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Author:宁纪锋 |
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Description: A simple example showing how to track an object with particle filter. Likelihood is based on Bhattacharya distance of color histogram. Platform: |
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Author:sofi |
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Description: 采用 CAMSHIFT 算法快速跟踪和检测运动目标的 C/C++ 源代码，OPENCV BETA 4.0 版本在其 SAMPLE 中给出了这个例子。算法的简单描述如下-This application demonstrates a fast, simple color tracking algorithm that can be used to track faces, hands . The CAMSHIFT algorithm is a modification of the Meanshift algorithm which is a robust statistical method of finding the mode (top) of a probability distribution. Both CAMSHIFT and Meanshift algorithms exist in the library. While it is a very fast and simple method of tracking, because CAMSHIFT tracks the center and size of the probability distribution of an object, it is only as good as the probability distribution that you produce for the object. Typically the probability distribution is derived from color via a histogram, although it could be produced from correlation, recognition scores or bolstered by frame differencing or motion detection schemes, or joint probabilities of different colors/motions etc.
In this application, we use only the most simplistic approach: A 1-D Hue histogram is sampled from the object in an HSV color space version of the image. To produce the Platform: |
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Author:黄文伟 |
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Description: 一个比较简单易懂的颜色直方图量化及转换的程序，适用于目标跟踪等领域，希望可以帮助有需要的人。-A relatively easy to understand and change the color histogram quantization procedures for tracking and other fields, hoping to help those in need. Platform: |
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Author:小吴 |
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Description: 得到图像的直方图来进行图像之间的比较，主要用于图像检索和目标跟踪-Carried out by the image histogram comparison between the images, mainly for image retrieval and object tracking Platform: |
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Author:zhangying |
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Description: 很牛的外国人写的跟踪算法，包括文章和源代码。文章名：Robust Fragments-based Tracking using the Integral Histogram-Is cattle tracking algorithm written by foreigners, including articles and source code. Article Name: Robust Fragments-based Tracking using the Integral Histogram Platform: |
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Author:dingph |
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Description: 这是一份用行人轮廓的分布直方图分类和识别步态的资料，不错的资料-This is a histogram with the pedestrian profile information classification and gait recognition, good information Platform: |
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Author:zhangbingbing |
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Search - histogram tracking