MIPOSE: a micro-intelligent platform for dynamic human pose recognition

ABSTRACTGiving computers the ability to learn from demonstrations is important for users to perform complex tasks. In this paper, we present an intelligent self-learning interface for dynamic human pose recognition. We capture 20 samples for an unknown pose to train a stable generative adversarial networks (GAN) system which aims to conduct data enhancement, then we adopt a threshold isolation method to distinguish relatively similar poses. A few minutes of learning time is sufficient to train a GAN system to successfully generate qualified pose samples. Our platform provides a feasible scheme for micro-intelligent interface, which can benefit to human-robot interaction greatly.