Performance improvement of deep learning based gesture recognition using spatiotemporal demosaicing technique
Paul K. J. Park, Baek Hwan Cho, Jin Man Park, Kyoobin Lee, Ha Young Kim, Hyo Ah Kang, Hyun Goo Lee, Jooyeon Woo, Yohan J. Roh, Won Jo Lee, Chang-Woo Shin, Qiang Wang, Hyunsurk Ryu · 2016
We propose a novel method for the demosaicing of event-based images that offers substantial performance improvement of far-distance gesture recognition based on deep Convolutional Neural Network. Unlike the conventional demosaicing technique using the spatial color interpolation of Bayer patterns, our new approach utilizes spatiotemporal correlation between pixel arrays, whereby timestamps of high-resolution pixels are efficiently generated in real-time from the event data. In this paper, we describe this new method and evaluate its performance with a hand motion recognition task.