实时跟踪手 [英] Real time tracking of hand
问题描述
我试图使用opencv实时检测和跟踪手。我认为哈尔级联分类器会产生公平的结果。分别用10k和20k的正和负图像训练后，我获得了一个分类器xml文件。不幸的是，它只在某些位置检测手，证明它只对刚性物体最有效。所以我现在正在考虑采用另一种算法，可以跟踪手，一旦通过haar分类器检测到。
I am trying to detect and track hand in real time using opencv. I thought haar cascade classifiers would yield a fair result. After training with 10k and 20k positive and negative images respectively, I obtained a classifier xml file. Unfortunately, it detects hand only in certain positions, proving that it works best only for rigid objects. So I am now thinking of adopting another algorithm that can track hand, once detected through haar classifier.
我的问题是，如果我确保haar分类器检测到某些框架，某个位置，什么方法会产生手的进一步的鲁棒跟踪？
My question is,if I make sure that haar classifier detects hand in a certain frame, certain position, what method would yield robust tracking of hand further?
我搜索web一点，并且理解我可以去检测手的光流，或卡尔曼滤波器或粒子滤波器，但也已经遇到自己的缺点。
I searched web a bit, and have understood I can go for optical flow of the detected hand , or kalman filter or particle filter, but also have come across their own disadvantages.
也，如果我结合立体视觉，它会帮助我，
also, If I incorporate stereo vision, would it help me, as I can possibly reconstruct hand in 3d.
推荐答案
您正确地认为哈尔功能 - 当它涉及到非刚性对象。
You concluded rightly about Haar features - they aren't that useful when it comes to non-rigid objects.
查看以下使用肤色检测手的文件。
Take a look at the following papers which use skin colour to detect hands.
- Interaction between hands and wearable cameras
- Markerless inspection of augmented reality objects
，本文使用KLT功能在第一次检测后跟踪手：
and this paper that uses KLT features to track the hand after the first detection:
我会说，立体相机不会帮助你的原因很多，因为非刚性对象的3D重建不直接，需要大量的创新和发展。但是，您可以查看手势估计部分中的论文页面，如果您要追踪3D追踪。
I would say that a stereo camera will not help your cause much, as 3D reconstruction of non-rigid objects isn't straightforward and would require a whole lot of innovation and development. However, you can take a look at the papers in the hand pose estimation section of this page if you wish to pursue 3D tracking.
编辑：同样看看这最近的论文，似乎得到了好的结果。
Also take a look at this recent paper, which seems to get good results.
这篇关于实时跟踪手的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！
