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Virtual reality using gesture recognition for deck operation training

机译:使用手势识别进行甲板操作培训的虚拟现实

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Operation training in simulator environment is an important part of maritime personnel competence building. Offshore simulators provide realistic visualizations which allow the users to immerse within the scenario. However, currently joysticks and keyboards are used as input devices for deck operation training. This approach limits the user experience - the trainees do not practice the gestures that they should be giving to the crane operators. Conversations with operation experts reveal that trying and experiencing the gestures is an important step of the practical training. To address this problem, we are building a gesture recognition system that allows the training participants to use natural gestures: move their body and hands as they would during a real operation. The movement is analyzed and gestures are detected using Microsoft Kinect sensor. We have implemented a prototype of a gesture recognition system, and have recorded data set of 15 people performing the gestures. Currently we are in the process of improving the system by training the recognition algorithms with recorded data. We believe, this is an important step towards high-quality training of maritime deck operations in immersive simulator environment.
机译:模拟器环境下的操作培训是海事人员能力建设的重要组成部分。离岸模拟器提供了逼真的可视化效果,使用户可以沉浸在场景中。然而,当前操纵杆和键盘被用作甲板操作训练的输入设备。这种方法限制了用户体验-受训人员没有练习应给予起重机操作员的手势。与操作专家的对话表明,尝试和体验手势是实践培训的重要一步。为了解决这个问题,我们正在构建一个手势识别系统,该系统允许培训参与者使用自然手势:像在实际操作中一样移动他们的身体和手。使用Microsoft Kinect传感器分析运动并检测手势。我们已经实现了手势识别系统的原型,并记录了执行手势的15个人的数据集。当前,我们正在通过训练带有记录数据的识别算法来改进系统。我们相信,这是在沉浸式仿真器环境中向高质量的海面甲板操作培训迈出的重要一步。

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