向非技术人员介绍AdaBoost算法 [英] Explaining the AdaBoost Algorithms to non-technical people

问题描述

我一直试图理解 AdaBoost算法并没有成功.我正在努力理解 Viola Jones的论文以人脸检测为例.

I've been trying to understand the AdaBoost algorithm without much success. I'm struggling with understanding the Viola Jones paper on Face Detection as an example.

您能用外行的术语解释AdaBoost并给出使用它的好例子吗?

Can you explain AdaBoost in laymen's terms and present good examples of when it's used?

推荐答案

AdaBoost使用大量训练样本图像(例如人脸)来选择许多良好的功能"/分类器".对于面部识别，分类器通常只是具有一定平均颜色值和相对大小的像素矩形. AdaBoost将研究许多分类器，并根据样本图像找出哪一个是人脸的最佳预测指标.选择最佳分类器后，它将继续寻找另一个分类器，直到达到某个阈值为止，并且那些分类器组合在一起将提供最终结果.

AdaBoost uses a number of training sample images (such as faces) to pick a number of good 'features'/'classifiers'. For face recognition a classifiers is typically just a rectangle of pixels that has a certain average color value and a relative size. AdaBoost will look at a number of classifiers and find out which one is the best predictor of a face based on the sample images. After it has chosen the best classifier it will continue to find another and another until some threshold is reached and those classifiers combined together will provide the end result.

您可能不想与非技术人员分享这部分内容:)，但还是很有趣.有几种数学技巧可以使AdaBoost快速进行人脸识别，例如能够将图像的所有颜色值相加并将其存储在二维数组中，从而使任何位置的值都等于所有像素的总和.并在该位置的左侧通过从右下角的值减去左上角的值并除以矩形中的像素数，此数组可用于非常快速地计算图像中任何矩形的平均颜色值.使用此技巧，您可以快速扫描整个图像，以查找与特定颜色匹配或接近的不同相对大小的矩形.

This part you may not want to share with non-technical people :) but it is interesting anyway. There are several mathematical tricks which make AdaBoost fast for face recognition such as the ability to add up all the color values of an image and store them in a 2 dimensional array so that the value in any position will be the sum of all the pixels up and to the left of that position. This array can be used to very quickly calculate the average color value of any rectangle within the image by subtracting the value found in the top left corner from the value found in the bottom right corner and dividing by the number of pixels in the rectangle. Using this trick you can quickly scan over an entire image looking for rectangles of different relative sizes that match or are close to a particular color.

希望这会有所帮助.

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