Institutional Repository
| Accurate gaze tracking from single camera using gabor corner detector | |
| Xia, L. (1); Sheng, Bin (1); Wu, Wen (2); Ma, Lizhuang (1); Li, Ping (3); Sheng, Bin | |
| 2014 | |
| 发表期刊 | Multimedia Tools and Applications
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| ISSN | 13807501 |
| 摘要 | Most of the existing gaze tracking schemes with high accuracy and high speed depend on infra-red (IR) lights and multi-cameras, which leads to high complexity of apparatus and high cost. Besides, many proposed approaches hardly offer a full discussion and solution of eye blink issue. In this paper, we propose a novel gaze tracking scheme which is capable of tracking eye movements in high accuracy. Our scheme incorporates the eye corner information extracted using a novel eye corner detector. This detector is developed based on the Gabor Wavelet Transform and the Structure Tensor. Gabor Wavelet Transform decomposes an image in multi-scales and multi-orientations, thus is robust against lighting variation and tiny shift. We abstract the distribution statistics of the feature points in the eye region and re-express it as a connectivity graph. Based on such abstraction we propose a novel solution to the eye blink issue which obtains a high successful detection rate. After implementation, our scheme is proven to be accurate compared with the state of the art. Notably, only one web camera is employed in our scheme without any auxiliary light source or cameras.; Most of the existing gaze tracking schemes with high accuracy and high speed depend on infra-red (IR) lights and multi-cameras, which leads to high complexity of apparatus and high cost. Besides, many proposed approaches hardly offer a full discussion and solution of eye blink issue. In this paper, we propose a novel gaze tracking scheme which is capable of tracking eye movements in high accuracy. Our scheme incorporates the eye corner information extracted using a novel eye corner detector. This detector is developed based on the Gabor Wavelet Transform and the Structure Tensor. Gabor Wavelet Transform decomposes an image in multi-scales and multi-orientations, thus is robust against lighting variation and tiny shift. We abstract the distribution statistics of the feature points in the eye region and re-express it as a connectivity graph. Based on such abstraction we propose a novel solution to the eye blink issue which obtains a high successful detection rate. After implementation, our scheme is proven to be accurate compared with the state of the art. Notably, only one web camera is employed in our scheme without any auxiliary light source or cameras. |
| 收录类别 | EI |
| 部门归属 | (1) Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, Shanghai, China; (2) Department of Computer and Information Science, Faculty of Science and Technology, University of Macau, Macao, China; (3) Department of Mathematics and Information Technology, The Hong Kong Institute of Education, Hong Kong, China; (4) The State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing, China |
| 语种 | 英语 |
| WOS记录号 | WOS:000367856500012 |
| 引用统计 | |
| 内容类型 | 期刊论文 |
| URI标识 | http://ir.iscas.ac.cn/handle/311060/17015 |
| 专题 | 中国科学院软件研究所 |
| 通讯作者 | Sheng, Bin |
| 推荐引用方式 GB/T 7714 | Xia, L. ,Sheng, Bin ,Wu, Wen ,et al. Accurate gaze tracking from single camera using gabor corner detector[J]. Multimedia Tools and Applications,2014. |
| APA | Xia, L. ,Sheng, Bin ,Wu, Wen ,Ma, Lizhuang ,Li, Ping ,&Sheng, Bin.(2014).Accurate gaze tracking from single camera using gabor corner detector.Multimedia Tools and Applications. |
| MLA | Xia, L. ,et al."Accurate gaze tracking from single camera using gabor corner detector".Multimedia Tools and Applications (2014). |
| 条目包含的文件 | 条目无相关文件。 | |||||
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