注册 登录  
 加关注
   显示下一条  |  关闭
温馨提示!由于新浪微博认证机制调整,您的新浪微博帐号绑定已过期,请重新绑定!立即重新绑定新浪微博》  |  关闭

dp: 生活的脚步,进步的点滴...

Cam、DSP、FPGA、PM、Life、More ...

 
 
 

日志

 
 

背景建模与前景检测之二(Background Generation And Foreground Detection Phase 2)   

2011-08-01 19:22:44|  分类: 默认分类 |  标签: |举报 |字号 订阅

  下载LOFTER 我的照片书  |


[19] D.Comaniciu, P.Meer, Mean shift: a robust approach toward feature space analysis, IEEE Transactions on Pattern Analysis and Machine Intelligence 24 (5) (2002) 603–619.
[20] I.Y.-H.Gu, V.Gui, Colour image segmentation using adaptive mean shift filters, in: International Conference on Image Processing, 2001, pp. 726–729.
[21] L.Yang, P.Meer, D.J.Foran, Unsupervised segmentation based on robust Estimation and color active contour models, IEEE Transactions on Information Technology in Biomedicine 9 (3) (2005) 475–486.
[22] D.Comaniciu, V.Ramesh, P.Meer, Kernel-based object tracking, IEEE Transactions on Pattern Analysis and Machine Intelligence 25 (5) (2003) 564– 577.
[23] R.T.Collins, Y.Liu, On-line selection of discrimin ative tracking features, in: International Conference on Computer Vision, 2003, pp. 346–352.

[24] R.Collins, Y.Liu, M.Leordeanu, On-line selection of discriminative tracking features, IEEE Transactions on Pattern Analysis and Machine Intelligence 27 (10) (2005) 1631–1643.
[25] O.Debeir, P.V.Ham, R.Kiss, C.Decaestecker, Tracking of migrating cells under phase-contrast video microscopy with combined mean-shift processes, IEEE Transactions on Medical Imaging 24 (6) (2005) 697–711.
[26] C.Shen, M.J.Brooks, A.van den Hengel, Fast global kernel density Mode seeking with application to localisation and tracking, in: International
Conference on Computer Vision, 2005, pp. 1516–1523.
[27] Intel open source computer vision library (2004).
URL http://www.intel.com/technology/computing/opencv/
[28] B.Lo, S.Velastin, Automatic congestion detection system for underground platforms, in: International Symposium on Intelligent Multimedia, Video and Speech Processing, Hong Kong, China, 2001, pp. 158–161.
[29] R.Cucchiara, C.Grana, M.Piccardi, A.Prati, Detecting moving objects, ghosts, and shadows in video streams, IEEE Transactions on Pattern Analysis and Machine Intelligence 25 (10) (2003) 1337–1342.
[30] IEEE international workshop on performance evaluation of tracking and surveillance (2000).
URL ftp://ftp.pets.rdg.ac.uk/pub/PETS2000/
[31] IEEE international workshop on performance evaluation of tracking and surveillance (2001).
URL ftp://ftp.pets.rdg.ac.uk/pub/PETS2001/
[32] IEEE international workshop on performance evaluation of tracking and surveillance (2006).
URL http://pets2006.net/data.html

写在最后的话

    本文所述的方法可说是像素级背景建模方式的巅峰之作。在接下来的时间里,我将尝试按照我自己的理解来实现文中的算法,对于论文中没有讲述透彻的部分,我也试图完善它。敬请期待~~

    在翻译文章的过程中得到了赵德斌博士的指导,在此表示感谢。

    同时,也感谢您耐心看完,希望对您有所帮助。

    欲知后事如何,且听下回分解。

网页中的文本编辑器不方便写公式,文中的公式恐怕很难看清楚,建议您下载本文的WORD文档


  评论这张
 
阅读(521)| 评论(0)
推荐

历史上的今天

在LOFTER的更多文章

评论

<#--最新日志,群博日志--> <#--推荐日志--> <#--引用记录--> <#--博主推荐--> <#--随机阅读--> <#--首页推荐--> <#--历史上的今天--> <#--被推荐日志--> <#--上一篇,下一篇--> <#-- 热度 --> <#-- 网易新闻广告 --> <#--右边模块结构--> <#--评论模块结构--> <#--引用模块结构--> <#--博主发起的投票-->
 
 
 
 
 
 
 
 
 
 
 
 
 
 

页脚

网易公司版权所有 ©1997-2016