Real-Time Gesture Recognition Using 3D Motion History Model
Real-Time Gesture Recognition Using 3D Motion History Model
复制标题
使用 3D 运动历史模型进行实时手势识别
DOI：
10.1007/11538059_92
复制
发表时间：
2005
期刊：
影响因子：
--
通讯作者：
Seong
中科院分区：
文献类型：
--
作者：
Ho;Sang;Seong
提出了一种基于三维运动历史模型的真实的手势识别方法。手势识别中存在两个难题：摄像机视角和手势持续时间。首先，我们解决了在单方向相机环境中非常困难的相机视图问题（例如，单目或立体照相机）。利用具有视差信息的三维MHM不仅解决了这一问题，而且提高了识别的可靠性和系统的可扩展性。其次，我们提出了动态历史缓冲（DHB），以解决持续时间的问题，从手势的速度变化，在每个执行时间。DHB使用运动幅度改善了问题。我们实现了一个实时系统，并进行手势识别实验。使用3D-MHM的系统比仅使用2D运动信息实现更好的识别结果。
In this paper, we present a novel method for real time gesture recognition with 3D Motion History Model (MHM). There are two difficult problems in gesture recognition: the camera view and the duration of gesture. First, we solved the camera view problem which is very difficult in the environment of single directional camera (e.g., monocular or stereo camera). Utilizing 3D-MHM with the disparity information, not only this problem is solved but also the reliability of recognition and the scalability of system are improved. Second, we proposed the dynamic history buffering (DHB) to solve the duration problem that comes from the variation of gesture velocity at every performing time. DHB improves the problem using magnitude of motion. We implemented a real-time system and performed gesture recognition experiments. The system using 3D-MHM achieves better results of recognition than using only 2D motion information.