학술논문

Performance improvement of deep learning based gesture recognition using spatiotemporal demosaicing technique
Document Type
Conference
Source
2016 IEEE International Conference on Image Processing (ICIP) Image Processing (ICIP), 2016 IEEE International Conference on. :1624-1628 Sep, 2016
Subject
Signal Processing and Analysis
Image resolution
Voltage control
Spatiotemporal phenomena
Correlation
Image recognition
Thumb
Interpolation
Dynamic Vision Sensor
motion
recognition
demosaicing
convolutional
neural network
Language
ISSN
2381-8549
Abstract
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.