We present a multi-stage pipeline for simple gesture recognition. The novelty of our approach is the association of different technologies, resulting in the first real-time system as of now to conjointly extract skeletons and recognise gesture on a Pepper robot. For this task, Pepper has been augmented with an embedded GPU for running deep CNNs and a fish-eye camera to capture whole scene interaction. We show in this article that real-case scenarios are challenging, and the state-of-the-art approaches hardly deal with unknown human gestures. We present here a way to handle such cases.
翻译：我们提出一个多阶段的简单姿态识别管道。我们方法的新颖之处在于不同技术的结合,导致迄今第一个联合提取骨骼并识别佩珀机器人的姿态的实时系统。为此任务,佩珀增加了一个内嵌的GPU,用于运行深层CNN,以及一个拍摄整个场景互动的鱼眼摄影机。我们在这个文章中显示,真实的情景是具有挑战性的,最先进的方法几乎无法处理未知的人类姿态。我们在这里提出了一个处理此类案例的方法。
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