Research Article
Improved Capsule Network for Gaze Estimation in Wireless Sensor Networks
@INPROCEEDINGS{10.4108/eai.29-6-2019.2282839, author={Mingyuan Luo and Xi Liu and Wei Wang and Wei Huang}, title={Improved Capsule Network for Gaze Estimation in Wireless Sensor Networks}, proceedings={12th EAI International Conference on Mobile Multimedia Communications, Mobimedia 2019, 29th - 30th Jun 2019, Weihai, China}, publisher={EAI}, proceedings_a={MOBIMEDIA}, year={2019}, month={6}, keywords={gaze estimation capsule network multi-layer capsule network}, doi={10.4108/eai.29-6-2019.2282839} }- Mingyuan Luo
Xi Liu
Wei Wang
Wei Huang
Year: 2019
Improved Capsule Network for Gaze Estimation in Wireless Sensor Networks
MOBIMEDIA
EAI
DOI: 10.4108/eai.29-6-2019.2282839
Abstract
In this study, aiming at the problem of gaze estimation in the wireless sensor network in the car, we use image-based method to estimate gaze based on the single camera sensor. We use the deep learning model and propose the improved model from three aspects based on the original capsule network. The first is to increase the convolution layer, the second is to increase the capsule layer, and the third is to widen the capsule layer in the network. Through many contrast experiments, it is proved that the appropriate use of the first or second improved method can achieve performance over other comparison models, and the prediction results of gaze estimation are almost no different from the real gaze direction.
Copyright © 2019–2024 EAI