Image-Based Methods for Interaction with Head-Worn Worker-Assistance Systems

Saxen, Frerk and Rashid, Omer and Al-Hamadi, Ayoub and Adler, Simon and Kernchen, Alexa and Mecke, Rüdiger (2014) Image-Based Methods for Interaction with Head-Worn Worker-Assistance Systems. Journal of Intelligent Learning Systems and Applications, 06 (03). pp. 141-152. ISSN 2150-8402

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Abstract

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.

Item Type: Article
Subjects: STM Open Press > Medical Science
Depositing User: Unnamed user with email support@stmopenpress.com
Date Deposited: 27 Jan 2023 07:06
Last Modified: 24 Aug 2024 12:52
URI: http://journal.submissionpages.com/id/eprint/200

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