Eyes Tracking Method Based on Kalman Filter and Camshift Algorithm

WANG Li; HAO Xiao-li

Chinese

您当前的位置：

首页 >

文章列表页 >

Eyes Tracking Method Based on Kalman Filter and Camshift Algorithm

更新时间：2026-09-04

- Eyes Tracking Method Based on Kalman Filter and Camshift Algorithm
- Vol. 33, Issue 6, Pages: 109-112(2016)
- 作者机构：
  
  太原理工大学计算机科学与技术学院,山西,太原,030024
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2016
- 稿件说明：
移动端阅览
王丽, 郝晓丽. 基于Kalman滤波器和改进Camshift算法的双眼跟踪[J]. 微电子学与计算机, 2016, 33(6): 109-112.

WANG Li, HAO Xiao-li. Eyes Tracking Method Based on Kalman Filter and Camshift Algorithm[J]. 2016, 33(6): 109-112.
王丽, 郝晓丽. 基于Kalman滤波器和改进Camshift算法的双眼跟踪[J]. 微电子学与计算机, 2016, 33(6): 109-112. DOI：

WANG Li, HAO Xiao-li. Eyes Tracking Method Based on Kalman Filter and Camshift Algorithm[J]. 2016, 33(6): 109-112. DOI：

摘要

针对目前的人眼跟踪方法对人脸尺度变化、人眼部分遮挡和头部旋转等情况过于敏感

经常因丢失目标而导致跟踪失败

提出一种综合运用Kalman滤波器和改进Camshift算法的双眼跟踪方法

该方法首先运用Kalman滤波器预测双眼在当前帧图像中的位置; 其次以该位置为中心运用改进Camshift迭代算法搜索双眼目标; 再利用双眼分布的对称性校正搜索到的双眼窗口; 最后更新Kalman滤波器和人眼模板.实验证明该方法对上述情况具有较强的鲁棒性.

Abstract

In view of the current eye tracking methods were too sensitive to conditions that face scale variations

partial occlusion of eye and head rotations in horizontality and verticality

which often resulted in tracking failure for the loss of objects. One eyes tracking method was proposed that was based on Kalman filter and improved Camshift algorithm. Firstly

predict the position of the eyes in the current image by Kalman filter; secondly

search the eyes region by Camshift iteration algorithm at the center of predicted position; thirdly

adjust the search window in the light of the symmetry of the of eyes; finally

update Kalman filter and the eyes templates. The experimental results show this method is robustness to those proposed conditions.

关键词

Keywords

references

Jesorsky O, Kirchberg K J, Frischholz R W. Robust face detection using the hausdorff distance[C]//third international conference AVBPA. Halmstal, Sweden: IEEE, 2001: 90-95.

Murawski K, Ró04anowski K, Krej M. Research and parameter optimization of the pattern recognition algorithm for the eye tracking infrared sensor[J]. Acta Physica Polonica, 2013, 124(3): 513-516. DOI: 513

李振龙, 李翔, 秦佳丽. 基于Camshift算法的虹膜实时跟踪[J]. 科学技术与工程, 2014, 14(13): 225-230. DOI: 225

刘春辉. 基于模板匹配和LK的人眼跟踪研究[D]. 天津: 天津大学, 2012.

Wang L S, Xie Y. Attention bias during processing of facial expressions in trait anxiety: An eye-tracking study[C]//Electronics and Optoelectronics (ICEOE), 2011 International Conference on. Dalian: IEEE, 2011: 347-350.

陈艳琴, 罗大庸. 基于Kalman滤波和Mean Shift算法的人眼实时跟踪[J]. 模式识别与人工智能, 2004, 17(2): 173-177. DOI: 173

郭君斌, 郭晓松, 雷磊, 等. 基于改进粒子滤波算法的人眼跟踪方法[J]. 仪器仪表学报, 2010, 31(8): 1720-1725. DOI: 1720

杨智勇, 蒲亦非, 巩晓倩, 等. 疲劳驾驶检测中人眼实时定位与跟踪[J]. 微电子学与计算机, 2014, 31 (8): 115-118. DOI: 115

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

A review of large model development: technological evolution from BERT to Deepseek

A high-efficiency charge pump for ultra-low voltage boost systems

Aerial small object detection algorithm based on improved RT-DETR

Design of ultra-low power real-time clock circuits

A feature-oriented context understanding and slice analysis network for tuberculosis detection

Related Author

No data

Related Institution

No data

AI问答

Postal code：100079
Tel：（010）53879206 Email：tmw@bjxintong.com.cn
Technical support is provided by Beijing Founder electronics co., LTD 京ICP备09082226号-64 京公网安备11010602201714号
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰