凝视
人工智能
卷积神经网络
计算机科学
计算机视觉
眼动
光学(聚焦)
集合(抽象数据类型)
任务(项目管理)
数据集
点(几何)
深度学习
数学
工程类
物理
光学
程序设计语言
系统工程
几何学
作者
Dongze Lian,Lina Hu,Weixin Luo,Yanyu Xu,Lixin Duan,Jingyi Yu,Shenghua Gao
出处
期刊:IEEE transactions on neural networks and learning systems
[Institute of Electrical and Electronics Engineers]
日期:2018-09-03
卷期号:30 (10): 3010-3023
被引量:63
标识
DOI:10.1109/tnnls.2018.2865525
摘要
Gaze estimation, which aims to predict gaze points with given eye images, is an important task in computer vision because of its applications in human visual attention understanding. Many existing methods are based on a single camera, and most of them only focus on either the gaze point estimation or gaze direction estimation. In this paper, we propose a novel multitask method for the gaze point estimation using multiview cameras. Specifically, we analyze the close relationship between the gaze point estimation and gaze direction estimation, and we use a partially shared convolutional neural networks architecture to simultaneously estimate the gaze direction and gaze point. Furthermore, we also introduce a new multiview gaze tracking data set that consists of multiview eye images of different subjects. As far as we know, it is the largest multiview gaze tracking data set. Comprehensive experiments on our multiview gaze tracking data set and existing data sets demonstrate that our multiview multitask gaze point estimation solution consistently outperforms existing methods.
科研通智能强力驱动
Strongly Powered by AbleSci AI