首页> 美国卫生研究院文献>Sensors (Basel Switzerland) >Combined Dynamic Time Warping with Multiple Sensors for 3D Gesture Recognition
【2h】

Combined Dynamic Time Warping with Multiple Sensors for 3D Gesture Recognition

机译:结合了动态时间扭曲和多个传感器的3D手势识别

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

Cyber-physical systems, which closely integrate physical systems and humans, can be applied to a wider range of applications through user movement analysis. In three-dimensional (3D) gesture recognition, multiple sensors are required to recognize various natural gestures. Several studies have been undertaken in the field of gesture recognition; however, gesture recognition was conducted based on data captured from various independent sensors, which rendered the capture and combination of real-time data complicated. In this study, a 3D gesture recognition method using combined information obtained from multiple sensors is proposed. The proposed method can robustly perform gesture recognition regardless of a user’s location and movement directions by providing viewpoint-weighted values and/or motion-weighted values. In the proposed method, the viewpoint-weighted dynamic time warping with multiple sensors has enhanced performance by preventing joint measurement errors and noise due to sensor measurement tolerance, which has resulted in the enhancement of recognition performance by comparing multiple joint sequences effectively.
机译:网络物理系统将物理系统和人类紧密集成在一起,可以通过用户移动分析将其应用于更广泛的应用程序中。在三维(3D)手势识别中,需要多个传感器来识别各种自然手势。在手势识别领域已经进行了一些研究。然而,手势识别是基于从各种独立传感器捕获的数据进行的,这使得实时数据的捕获和组合变得复杂。在这项研究中,提出了一种使用从多个传感器获得的组合信息的3D手势识别方法。通过提供视点加权值和/或运动加权值,无论用户的位置和运动方向如何,所提出的方法都可以可靠地执行手势识别。在所提出的方法中,通过防止由于传感器测量公差引起的关节测量误差和噪声,具有多个传感器的视点加权动态时间扭曲具有增强的性能,这导致通过有效地比较多个关节序列而增强了识别性能。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号