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Conference Papers Year : 2017

HCI Based on Gesture Recognition in an Augmented Reality System for Diagnosis Planning and Training

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Abstract

An Augmented Reality System for Coronary Artery Diagnosis Planning and Training (ARS-CADPT) is designed and realized in this paper. As the characteristic of ARS-CADPT, the algorithms of static gesture recognition and dynamic gesture spotting and recognition are presented to realize the real-time and friendly Human-Computer Interaction (HCI). The experimental results show that, with the use of ARS-CADPT, the HCI is natural and fluent, which improves the user’s immersion and improves the diagnosis and training effects.
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Dates and versions

hal-01820905 , version 1 (22-06-2018)

Licence

Attribution - CC BY 4.0

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Qiming Li, Chen Huang, Zeyu Li, Yimin Chen, Lizhuang Ma. HCI Based on Gesture Recognition in an Augmented Reality System for Diagnosis Planning and Training. 2nd International Conference on Intelligence Science (ICIS), Oct 2017, Shanghai, China. pp.113-123, ⟨10.1007/978-3-319-68121-4_12⟩. ⟨hal-01820905⟩
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