首页> 外文期刊>IEEE Transactions on Consumer Electronics >An Incremental Learning Based Gesture Recognition System for Consumer Devices Using Edge-Fog Computing
【24h】

An Incremental Learning Based Gesture Recognition System for Consumer Devices Using Edge-Fog Computing

机译:使用边缘雾计算的消费者设备的基于增量学习的手势识别系统

获取原文
获取原文并翻译 | 示例
           

摘要

Gesture based systems are attracting more and more researchers to develop a single point control for consumer devices. Most of the existing works use wearable devices or camera based solutions, thus requiring additional resources. This paper presents an incremental learning based gesture recognition system that uses gyroscope sensor of Edge device (mobile phone) to recognize gesture of user and select the function of consumer device. Accelerometer sensor of the mobile phone is then used to control the magnitude of the selected function. User also gives speech input along with the gesture, which is recognized by the Fog device (laptop) and its result is used by the system for incremental learning. The system is implemented by developing an application on the mobile phone and various experiments are performed for validating the accuracy of the system.
机译:基于手势的系统吸引了越来越多的研究人员,为消费者设备开发单点控制。大多数现有工程使用可穿戴设备或基于相机的解决方案,从而需要额外的资源。本文介绍了一种基于增量学习的手势识别系统,它使用边缘设备(移动电话)的陀螺仪传感器来识别用户的手势并选择消费者设备的功能。然后使用移动电话的加速度计传感器来控制所选功能的幅度。用户还提供语音输入以及由雾设备(笔记本电脑)识别的手势以及其结果由系统用于增量学习。该系统通过在移动电话上开发应用来实现,并且执行各种实验以验证系统的准确性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

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