Realtime and Accurate 3D Eye Gaze Capture with DCNN-Based Iris and Pupil Segmentation
文献类型：期刊论文
| 作者 | Wang, Zhiyong1,3; Chai, Jinxiang2; Xia, Shihong1,3 |
| 刊名 | IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
 |
| 出版日期 | 2021 |
| 卷号 | 27期号:1页码:190-203 |
| 关键词 | Three-dimensional displays Gaze tracking Iris Cameras Convolutional neural nets Image reconstruction Videos 3D eye gaze tracking convolutional neural network facial capture |
| ISSN号 | 1077-2626 |
| DOI | 10.1109/TVCG.2019.2938165 |
| 英文摘要 | This paper presents a realtime and accurate method for 3D eye gaze tracking with a monocular RGB camera. Our key idea is to train a deep convolutional neural network(DCNN) that automatically extracts the iris and pupil pixels of each eye from input images. To achieve this goal, we combine the power of Unet [1] and Squeezenet [2] to train an efficient convolutional neural network for pixel classification. In addition, we track the 3D eye gaze state in the Maximum A Posteriori (MAP) framework, which sequentially searches for the most likely state of the 3D eye gaze at each frame. When eye blinking occurs, the eye gaze tracker can obtain an inaccurate result. We further extend the convolutional neural network for eye close detection in order to improve the robustness and accuracy of the eye gaze tracker. Our system runs in realtime on desktop PCs and smart phones. We have evaluated our system on live videos and Internet videos, and our results demonstrate that the system is robust and accurate for various genders, races, lighting conditions, poses, shapes and facial expressions. A comparison against Wang et al. [3] shows that our method advances the state of the art in 3D eye tracking using a single RGB camera. |
| 资助项目 | Natural Science Foundation of Beijing Municipality[L182052] ; National Natural Science Foundation of China[61772499] |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000594242000015 |
| 出版者 | IEEE COMPUTER SOC |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/16532]  |
| 专题 | 中国科学院计算技术研究所期刊论文_英文 |
| 通讯作者 | Chai, Jinxiang; Xia, Shihong |
| 作者单位 | 1.Chinese Acad Sci, Inst Comp Technol, Beijing Key Lab Mobile Comp & Pervas Device, Beijing 100190, Peoples R China 2.Texas A&M Univ, College Stn, TX 77843 USA 3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wang, Zhiyong,Chai, Jinxiang,Xia, Shihong. Realtime and Accurate 3D Eye Gaze Capture with DCNN-Based Iris and Pupil Segmentation[J]. IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS,2021,27(1):190-203. |
| APA | Wang, Zhiyong,Chai, Jinxiang,&Xia, Shihong.(2021).Realtime and Accurate 3D Eye Gaze Capture with DCNN-Based Iris and Pupil Segmentation.IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS,27(1),190-203. |
| MLA | Wang, Zhiyong,et al."Realtime and Accurate 3D Eye Gaze Capture with DCNN-Based Iris and Pupil Segmentation".IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 27.1(2021):190-203. |
入库方式： OAI收割
来源：计算技术研究所
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