lixiaoguang20的博客

GoalIn this chapter,We will understand the concepts of optical flow and its estimation using Lucas-Kanade method. We will use functions likecv.calcOpticalFlowPyrLK()to track feature points in a...

In this post, we will learn how to implement a simple Video Stabilizer using a technique called Point Feature Matching in OpenCV library.We will discuss the algorithm and share the code(in python) to...

In today’s post, we will learn how to recognize text in images using an open source tool calledTesseractand OpenCV. The method of extracting text from images is also called Optical Character Recogni...

There is a common saying,“A picture is worth a thousand words“. In this post, we are going to take that literally and try to find the words in a picture! In an earlier post aboutText Recognition, we...

In this tutorial, we will discuss an interesting application of Deep Learning applied to faces. We will estimate the age and figure out the gender of the person from a single image. The model is train...

In today’s post, we are covering the topic of Gaze Estimation and Tracking.I was invited to give a talk on the subject at a workshop onEye Tracking for AR and VRorganized by Facebook Research at t...

从下述几篇文章中总结： - OpenCV中Adaboost训练的经验总结 - 采用opencv_cascadetrain进行训练的步骤及注意事项 - 使用opencv_traincascade训练遇到的问题总汇在讲下面内容时首先应先清楚一件事情，自己收集到的原始负样本和参与训练的负样本(numNeg)不是同一个概念，两者无必然联系，通过在原始负样本图像上滑动和scale

前段时间学习了HOG描述子及其与SVM结合在行人检测方面的应用。当我们用训练好的模型去检测测试图像时，我们会用到detectMultiScale() 这个函数来对图像进行多尺度检测。这是opencv3.1里的参数解释可以看到一共有8个参数。1.img(必需)这个不用多解释，显然是要输入的图像。图像可以是彩色也可以是灰度的。2.foundLoc

人脸检测一种主流的方法就是类haar+adaboosting，opencv中也是用的这种方法。这种方法可以推广到刚性物体的检测，前提是要训练好级联分类器(比如说用类haar特征)，一旦训练数据弄好了，直接调用opencv中的类CascadeClassifier，用它的几个简单的成员函数就可以完成检测功能。所以说用起来还是很简单的。下面就是用的opencv中自带的samples中的facedetec

以OpenCV训练级联Adaboost为例进行说明numPos: 12000numNeg: 120000numStages: 15precalcValBufSize[Mb] : 1000precalcIdxBufSize[Mb] : 800stageType: BOOSTfeatureType: HOGsampleWidth: 40