摘要: Appearance-based gaze estimation has attracted more and more attention because of its wide range of applications. The use of deep convolutional neural networks has improved the accuracy...关键词: Appearance-based gaze estimation Dilated-convolutions ...
Figure 1 provides an overview of our proposed method for in-the-wild appearance-based gaze estimation using multimodal convolutional neural networks (CNN). We first employ state-of-the-art face detection and facial landmark detection methods to locate landmarks in the input image obtained from th...
论文链接:Learning-by-Synthesis for Appearance-Based 3D Gaze Estimation 简介: 视线可以判断人眼注意力,但一般的穿戴设备难以获得高分辨率人眼图像,解决低分辨率视线估计是一个发展方向。基于外观的三维视线估计被定义为一个有监督的回归任务,用于根据输入特征(即一组眼睛图像和一组三维头部姿势)预测三维视线方向。基于...
介绍了一种使用了CNN作为主要方法的Gaze Estimation方法。 在多个数据集上使用多种方法进行分析比较,以得到更多对于Gaze Estimation的新理解。 论文主要内容 MPIIGaze数据集 论文作者在文中提到,大部分(截至论文撰写时的)主流Gaze Estimating方法往往基于实验室中受控的环境下采集的数据集,而这类数据集的眼部外表往往变化...
convolutional networks),上篇博客总结的方法(Appearancebased gaze estimation in the wild),iTracker,只考虑双眼部分的iTracker,修改为AlexNet的ITracker。 在与两个数据集,2D与3D两种问题的对比上,论文作者提出的空间权重CNN方法均取得了最好的表现。其中,2D问题上各方法在EYEDIAP数据集上的准确率均低于MPIIGaze数据集,...
1: Overview of GazeNet– appearance-based gaze estimationusing a deep convolutional neural network (CNN).This work aims to shed light on these questions and makethe next step towards unconstrained gaze estimation. To facilitatecross-dataset evaluations, we f i rst introduce the MPIIGaze dataset,...
3Dgazeestimationineverydayenvironmentsandwithoutanyassumptionsregardingusers’facialappearance,geometricpropertiesoftheenvironmentandcamera,orimageformationpropertiesofthecameraitself.UnconstrainedgazeestimationusingmonocularRGB cameras is particularly promising given the proliferation of such cameras in portable devices [8...
Gaze estimationEye appearance Asymmetric regressionEye gaze estimation has been increasingly demanded by recent intelligent systems to accomplish a range of interaction-related tasks, by using simple eye images as input. However, learning the highly......
Revisiting Data Normalization for Appearance-Based Gaze Estimation - Max Planck Institute for Informatics 解决的问题 基于外观的视线估计方式中,头部姿态和相机拍摄距离的多样性不利于训练的收敛。前期工作通过将输入图像和视线映射到归一化空间,来消除这种三维空间中的多变性,但该种方法的有效性没有明确定论。
本周的主要任务是利用cnn完成视线追踪模型的初步训练,根据论文Appearance-Based Gaze Estimation in the Wild中的实现方法(如下图),我们本周在未进行图像处理的前提下,通过将眼部图像直接喂入cnn进行了初步的训练。 训练采用的数据集为论文中提供的MPIIGaze数据集,在直接使用眼睛图像训练过程中只采用了数据集中左眼的数...