期刊文献+

Tracking of human head with particle filter 被引量:1

Tracking of human head with particle filter
下载PDF
导出
摘要 To cope with the problem of tracking a human head in a complicated scene,we propose a method that adopts human skin color and hair color integrated with a kind of particle filter named condensation algorithm.Firstly,a novel method is presented to set up human head color model using skin color and hair color separately based on region growing.Compared with traditional human face model,this method is more precise and works well when human turns around and the face disappears in the image.Then a novel method is presented to use color model in condensation algorithm more effectively.In this method,a combination of edge detection result,color segmentation result and color edge detection result in an Omega window is used to measure the scale and position of human head in condensation.Experiments show that this approach can track human head in complicated scene even when human turns around or the distance of tracking a human head changes quickly. To cope with the problem of tracking a human head in a complicated scene, we propose a method that adopts human skin color and hair color integrated with a kind of particle filter named condensation algorithm. Firstly, a novel method is presented to set up human head color model using skin color and hair color separately based on region growing. Compared with traditional human face model, this method is more precise and works well when human turns around and the face disappears in the image. Then a novel method is presented to use color model in condensation algorithm more effectively. In this method, a combination of edge detection result, color segmentation result and color edge detection result in an Omega window is used to measure the scale and position of human head in condensation. Experiments show that this approach can track human head in complicated scene even when human turns around or the distance of tracking a human head changes quickly.
作者 郭超
出处 《Journal of Harbin Institute of Technology(New Series)》 EI CAS 2009年第2期269-274,共6页 哈尔滨工业大学学报(英文版)
关键词 human head tracking CONDENSATION particle filter Hausdorff distance 粒子滤波算法 距离跟踪 人类 头部 皮肤颜色 彩色边缘检测 颜色模式 人脸模型
  • 相关文献

同被引文献17

  • 1Chee B C. Detection and Monitoring of Passengers on a Bus by Video Surveillance [ C ]//Proceedings of 14th International Conference on Image Analysis and Processing,2007:143-148. 被引量:1
  • 2Han H, Ding Y, Hao K. A New Immune Particle Filter Algorithm for Tracking a Moving Target [ C ]//Proeedings of 6th Interna- tional Conference on Natural Computation,2010:3248-3252. 被引量:1
  • 3Zhong Z, Xu Y. Crowd Energy and Feature Analysis [ C ]// Proceedings of IEEE International Conference on Integration Technology, 2007 : 144 - 150. 被引量:1
  • 4Elhabian S, Ali A, Farag A. Face Recognition at-a-Distance using Texture Sparse-Stereo and Dense-Stereo [ C ]//International Conference on Multimedia Technology ,2011:6690-6695. 被引量:1
  • 5Czyzewski A. Examining Kalman Filters Applied to Tracking Objects in Motion [ C ]//Proceedings of the 9th International Workshop on Image Analysis for Multimedia Interactive Services ,2008:175-178. 被引量:1
  • 6Talele K T, Kadam S. Face Detection and Geometric Face Normali- zation [ C ]//Proceedings of IEEE Region 10 Conference ,2009 : 1-6. 被引量:1
  • 7Li M, Zhang Z, Huang K, et al. Estimating the Number of People in Crowded Scenes by MID Based Foreground Segmentation and Head-Shoulder Detection [ C ]//Proceedings of International Conference on Pattern Recognition ,2008,1 : 1-4. 被引量:1
  • 8Fan H,Zhu L L,Tang Y D. An Extended Set of Haar-Like Features for Rapid Object Detection [ C ]//Proceedings of IEEE International Conference on Image Processing,2002,1:900-903. 被引量:1
  • 9Guo L,Ge P S,Zhang M H,et al. Pedestrian Detection for Intelligent Transportation Systems Combining AdaBoost Algorithm and Support Vector Machine [ J ]. Expert Systems with Applications, 2012,39 (4) :4274-4286. 被引量:1
  • 10Nguyen N T, Phung D Q. Learning and Detecting Activities from Movement Trajectories Using the Hierarchical Hidden Markov Models[ C ]//Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition,2005,2:955-960. 被引量:1

引证文献1

二级引证文献4

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