Description: 基于Processed histogram的人脸识别方法，方法简单，识别率高，参考文献“Face Recognition using processed histogram and phase only correlation”-Recognizing objects from large image databases, histogram based methods have proved simplicity and usefulness in last decade. Initially, this idea was based on color histograms that were launched by swain. This algorithm presents the first part of our proposed technique named as “Histogram processed Face Recognition”. Platform: |
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Author:GJ |
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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: |
Size: 15360 |
Author:黄文伟 |
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Description: 压缩包包括以下几个功能实现的opencv源代码：canny边缘检测算法实现、高斯背景建模、背景差分法实现边缘检测、图像颜色分布直方图的相关处理、人脸识别算法的实现。-Compressed package includes the following functions to achieve the opencv source code: canny edge detection algorithm, Gaussian background modeling, background subtraction method for edge detection, image color distribution histogram of the correlation processing, face recognition algorithm. Platform: |
Size: 6144 |
Author:张桦 |
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Description: 人脸肤色检测，在转换成Ycbcr格式后用相关系数进行肤色似然度计算，检测属于肤色的像素。-Skin color detection, the conversion into Ycbcr format color by correlation coefficients calculated likelihood, detection is skin color pixels. Platform: |
Size: 1024 |
Author:飞哥 |
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Description: 在彩色空间中，皮肤颜色的分布较为集中，与其他景物颜色间有较好的可区分性，可以用模型描述或对样本进行学习的方法加以判别。图像中皮肤颜色的差异主要由光照引起，在检测中只考虑色度信息，就可以减少光照的影响，使肤色的分布更趋集中。通过检测皮肤区域，可以缩小人脸的搜索范围，提高检测速度。HSV空间是RGB空间的非线性变换，它将原本相关性很强的R、G、B值转换为相关性较弱的H、S、V值，H和S分量与人感受色彩的方式相一致。HSV颜色空间可以用一个圆锥空间模型来描述.-In the color space, the distribution of skin color is more concentrated, have better sex with other distinguishable color scene, you can use the model to describe or samples to determine the method of learning. Differences in skin color image is mainly caused by light, in the detection consider only the chrominance information, you can reduce the effects of light, so that the distribution of color become more concentrated. By detecting an area of skin, the face can reduce the search range, to improve the detection speed. HSV space is a non-linear transformation of the RGB color space, it is a strong correlation between the original R, G, B values are converted to a weak correlation of H, S, V values, H and S component and the way people feel consistent color . HSV color space model can be used to describe a conical space Platform: |
Size: 1890304 |
Author:xc |
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Description: 已知多个时间序列两两之间的相关性系数，采用相关性颜色图表示-The correlation of multiplt time series data, and these correlation is displayed by the correlation color map Platform: |
Size: 1024 |
Author:比利 |
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Description: 自己根据公式编写的颜色矩特征，纹理空间自相关函数特征(The color moment feature and texture space auto correlation function feature written by the formula.) Platform: |
Size: 44032 |
Author:独孤冷歆
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Description: ASMS仅依靠颜色特征的算法而且速度很快，在VOT2015是20名, 是VOT2015官方推荐的实时算法，平均帧率125FPS。在VOT2016是32名，整体属于中等水平。在经典mean-shift框架下加入了尺度估计，经典颜色直方图特征，加入了两个先验(尺度不剧变+可能偏最大)作为正则项，和反向尺度一致性检查。在相关滤波和深度学习盛行的年代，还能看到mean-shift打榜还有如此高的性价比实在不容易。环境：WIN8.1 64位 +Visual Studio 2015 +OpenCV 3.3.0(ASMS relies only on the color feature algorithm and is fast in speed. It is 20 in VOT2015, a real-time algorithm recommended by the VOT2015, with an average frame rate of 125FPS. The VOT2016 is 32, and the whole is at the middle level. In the classical mean-shift framework, scale estimation is added. Classical color histogram features are added to two priors (scale undrastic + possible maximum) as regularization terms and reverse scale consistency check. In the age of correlation filtering and depth learning, it was also not easy to see that mean-shift had such a high cost performance.) Platform: |
Size: 7051264 |
Author:betforever |
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Search - color by correlation