Depth-Based Hand Pose Segmentation with Hough Random Forest
Depth-Based Hand Pose Segmentation with Hough Random Forest
复制标题
使用霍夫随机森林进行基于深度的手势分割
DOI：
--
复制
发表时间：
2016
期刊：
影响因子：
--
通讯作者：
K. W. Lin
中科院分区：
文献类型：
--
作者：
Wei;Ju;K. W. Lin
随着图像处理和计算机视觉技术的发展，利用手势与机器进行交流将不再仅仅出现在科学活动中，也不再仅仅是一个概念性的产品。手势识别是计算机科学和语言技术中的一个主题，目标是通过数学算法解释人类手势。有了这个，我们可以有一个更方便的生活。因此，我们的目标是使用图像处理算法来有效地识别正确的手势从相机和提出一个用户友好的人机界面。近年来，手势识别已成为一个热门和重要的问题。它可用于机器人控制、电器控制、游戏控制等。我们提出了一种算法，能够正确计算准确的手指关节位置，然后评估手势。该算法分为两个部分：手部位置检测和手势识别。在手势检测中，我们从深度摄像头获取深度图像，解决了光照和背景带来的问题。在手势识别中，我们使用一个目标识别算法，将较难的手指运动评估问题转化为较容易的投票分类问题。深度相机帮助我们的分类器避免了错误识别对象的照明问题。
With the development of image processing and computer vision technology, using gesture to communicate with the machine will not only appear in scientific move or just a conceptual product. Gesture recognition is a topic in computer science and language technology with the goal of interpreting human gestures via mathematical algorithms. With this, we can have a more convenient life. Therefore, our goal is using image processing algorithm to effectively recognize the correct gesture from camera and present a user-friendly human-machine interface. In recent years, gesture recognition has become a popular and important issue. It can be used for robot control, appliances control, gaming control, etc. We present an algorithm which is able to correctly calculate the accurate finger joint position and then evaluate the gesture. This algorithm is divided into two parts: hand position detection and gesture recognition. In gesture detection, we capture the depth image from depth camera to solve the problem caused by illumination and background. In gesture recognition, we use an object recognizing algorithm to make the difficult evaluating finger movement problem corresponds to an easier voting classify problem. Depth camera helps our classifier avoid the illumination problem from incorrectly recognizing object.