One shot learning gesture recognition with Kinect sensor

Di Wu, Fan Zhu, Ling Shao, Hui Zhang
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引用次数: 6

Abstract

Gestures are both natural and intuitive for Human-Computer-Interaction (HCI) and the one-shot learning scenario is one of the real world situations in terms of gesture recognition problems. In this demo, we present a hand gesture recognition system using the Kinect sensor, which addresses the problem of one-shot learning gesture recognition with a user-defined training and testing system. Such a system can behave like a remote control where the user can allocate a specific function using a prefered gesture by performing it only once. To adopt the gesture recognition framework, the system first automatically segments an action sequence into atomic tokens, and then adopts the Extended-Motion-History-Image (Extended-MHI) for motion feature representation. We evaluate the performance of our system quantitatively in Chalearn Gesture Challenge, and apply it to a virtual one shot learning gesture recognition system.
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用Kinect传感器学习手势识别
对于人机交互(HCI)来说,手势既自然又直观,一次性学习场景是手势识别问题的现实情况之一。在这个演示中,我们展示了一个使用Kinect传感器的手势识别系统,该系统通过用户定义的训练和测试系统解决了一次性学习手势识别的问题。这样的系统可以像一个遥控器,用户可以使用一个偏好的手势分配一个特定的功能,只需执行一次。采用手势识别框架时,系统首先自动将动作序列分割成原子标记,然后采用扩展运动历史图像(Extended-Motion-History-Image, Extended-MHI)来表示运动特征。我们在Chalearn手势挑战赛中定量评估了系统的性能,并将其应用于虚拟一次性学习手势识别系统。
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