CASIA OpenIR  > 智能感知与计算研究中心
Cast Shadow Removal Combining Local and Global Features
Liu Zhou; Kaiqi Huang; Tieniu Tan
2007
Conference NameCVPR workshop on the Seventh International Workshop on Visual Surveillance
Source PublicationCVPR workshop on the Seventh International Workshop on Visual Surveillance
Pages1-8
Conference Date2007-06-01
Conference PlaceMinneapolis, Minnesota, USA
AbstractIn this paper, we present a method using pixel-level information, local region-level information and global-level information to remove shadow. At the pixel-level, we employ GMM to model the behavior of cast shadow for every pixel in the HSV color space, as it can deal with complex illumination conditions. However, unlike the GMM for background which can obtain sample every frame, this model for shadow needs more frames to get the same number of sample, because shadow may not appear at the same pixel for each frame. Therefore, it will take a long time to converge. To overcome this drawback, we use the local region-level information to get more samples and global-level information to improve a preclassifier and then, by using it, we get samples which are more likely to be shadow. Also, at the local region-level, we use Markov random fields to represent dependencies between the label of single pixel and labels of its neighborhood. Moreover, to make global level information more robust, tracking information is used. Experimental results show that the proposed method is efficient and robust.
KeywordLocal And Global Features
Language英语
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/12724
Collection智能感知与计算研究中心
Corresponding AuthorKaiqi Huang
Affiliation中国科学院自动化研究所
Recommended Citation
GB/T 7714
Liu Zhou,Kaiqi Huang,Tieniu Tan. Cast Shadow Removal Combining Local and Global Features[C],2007:1-8.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Liu Zhou]'s Articles
[Kaiqi Huang]'s Articles
[Tieniu Tan]'s Articles
Baidu academic
Similar articles in Baidu academic
[Liu Zhou]'s Articles
[Kaiqi Huang]'s Articles
[Tieniu Tan]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Liu Zhou]'s Articles
[Kaiqi Huang]'s Articles
[Tieniu Tan]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.