期刊文献+

眼睛状态检测的组合方法 被引量:16

Combined Method of Eye States Detection
下载PDF
导出
摘要 眼睛状态的检测具有广泛的应用.详细介绍了5种检测眼睛状态的方法,即灰度模板方法、Fisher方法、投影的方法、找眼睛上眼睑的方法、用Hough变换找眼珠的方法.通过对这5种方法进行组合,提高了眼睛状态检测的准确率.通过对396个眼睛进行检测,准确率达到了95.2%.实验结果表明了这5种算法组合算法的有效性,抗光照能力强;同时适中的复杂性也说明了该组合算法的可行性. There are many applications of the robust eye states detection. In this paper, five methods are applied to detect the eye states in color eye images. They are gray model method, fisher method, projection method, detect-upper-eyelid method and detect-eyeball method. Each of the five methods has its advantage as well as its disadvantage. To increase the accuracy of detection, a combined method is proposed, which combines the above five methods so that it can take good advantage of them all. Experiments are done with 396 different human eyes, 264 of which are closed ones, and 377 of these experiments turned out satisfactory results. The accuracy reaches 95. 2 %. The inspiring outcome shows that the combined method is effective even if the illumination is nonlinear. At the same time, the combined method is practical because it is moderate in both time and space consuming. This paper introduces in details the idea of the five methods, the design of the combined algorithm, the experiments and their relevant results.
出处 《中国图象图形学报(A辑)》 CSCD 北大核心 2003年第10期1140-1145,共6页 Journal of Image and Graphics
基金 国家自然科学基金(60144001) 香港浸会大学基金 教育部留学回国人员科研启动基金
关键词 眼睛状态检测 HOUGH变换 灰度模板法 Fisher法 神经网络 Computer image processing, Eye states, Histogram equalization, Horizontal projection, Hough transform
  • 相关文献

参考文献11

  • 1[1]Lam K M, Yan H. Locating and extracting the eye in human face images[J]. Pattern Recognition, 1996,29(5):771~779.
  • 2[2]Yang M H, Kriegman D, Ahuja N. Detecting face in images: a survey[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002, 24(1):34~58.
  • 3[3]Lai J H, Yuen P C, Chen W S et al. Robust facial feature point detection under nonlinear illuminations [A]. In: Proceeding of IEEE ICCV (International Conference on Computer Vision )Workshop on Recognition, Analysis and Tracking of Faces and Gestures in Real-time Systems (RATFG-RTS 2001)[C],Vancouver, Canada, 2001:168 ~ 174.
  • 4[4]Yuille A, Hallinan P, Cohen D S. Feature extraction from faces using deformable templates [J]. International Journal of Computer Vision, 1992, 8(2):99~111.
  • 5[5]Deng J, Lai F. Region-based template deformation and masking for eyefeature extraction and description [J]. Pattern Recognition, 1997, 30(3) :403~419.
  • 6[6]Chow G, Li X. Towards a system for automatic facial feature detection[J]. Pattern Recognition, 1993, 26(12):1739~1755.
  • 7[7]Tian Y L, Kanade T, Cohn J F. Recognizing upper face actions for facial expression analysis[A]. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition(CVPR '00) [C]. Hilton Head Island, South Carolina, USA, 2000, 1:294~301.
  • 8[8]Tian Y L, Kanade T, Cohn J F. Eye state action unit detection by Gabor wavelets [C ]. The 3rd International Conference on Multi-modal Interfaces (ICMI'00)[C], Beijing, China, 2000:143~150.
  • 9[9]Tian Y L, Kanade T. Cohn J F. Dual-state parametric eye tracking [A]. In: Proceedings of the 4th IEEE International Conference on Automatic Face and Gesture Recognition(FG'00)[C], Grenoble, France, 2000 : 110~ 115.
  • 10[10]Liu H, Wu Y W, Zha H B. Eye state detection from color facial image sequence [A]. In: Second International Conference on Image and Graphics[C], Hefei, China, 2002: 693~ 698.

同被引文献119

引证文献16

二级引证文献45

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部