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  • 标题:Image-Based Methods for Interaction with Head-Worn Worker-Assistance Systems
  • 本地全文:下载
  • 作者:Frerk Saxen ; Omer Rashid ; Ayoub Al-Hamadi
  • 期刊名称:Journal of Intelligent Learning Systems and Applications
  • 印刷版ISSN:2150-8402
  • 电子版ISSN:2150-8410
  • 出版年度:2014
  • 卷号:06
  • 期号:03
  • 页码:141-152
  • DOI:10.4236/jilsa.2014.63011
  • 语种:English
  • 出版社:Scientific Research Publishing
  • 摘要:In this paper, a mobile assistance-system is described which supports users in performing manual working tasks in the context of assembling complex products. The assistance system contains a head-worn display for the visualization of information relevant for the workflow as well as a video camera to acquire the scene. This paper is focused on the interaction of the user with this system and describes work in progress and initial results from an industrial application scenario. We present image-based methods for robust recognition of static and dynamic hand gestures in realtime. These methods are used for an intuitive interaction with the assistance-system. The segmentation of the hand based on color information builds the basis of feature extraction for static and dynamic gestures. For the static gestures, the activation of particular sensitive regions in the camera image by the user’s hand is used for interaction. An HMM classifier is used to extract dynamic gestures depending on motion parameters determined based on the optical flow in the camera image.
  • 关键词:Head Mounted Display; Gesture Recognition; Mobile Assistance System
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