中国科学院光电技术研究所机构知识库
Advanced  
IOE OpenIR  > 自适应光学技术研究室(八室)  > 会议论文
题名:
Discriminative region extraction and feature selection based on the combination of SURF and saliency
作者: Deng Li; Wang Chunhong; Rao Changhui
出版日期: 2011
会议名称: Proceedings of SPIE - The International Society for Optical Engineering, v 8193, 2011, International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Infrared Imaging and Applications
会议日期: 2011
通讯作者: Deng Li
中文摘要: The objective of this paper is to provide a possible optimization on salient region algorithm, which is extensively used in recognizing and learning object categories. Salient region algorithm owns the superiority of intra-class tolerance, global score of features and automatically prominent scale selection under certain range. However, the major limitation behaves on performance, and that is what we attempt to improve. By reducing the number of pixels involved in saliency calculation, it can be accelerated. We use interest points detected by fast-Hessian, the detector of SURF, as the candidate feature for saliency operation, rather than the whole set in image. This implementation is thereby called Saliency based Optimization over SURF (SOSU for short). Experiment shows that bringing in of such a fast detector significantly speeds up the algorithm. Meanwhile, Robustness of intra-class diversity ensures object recognition accuracy.
英文摘要: The objective of this paper is to provide a possible optimization on salient region algorithm, which is extensively used in recognizing and learning object categories. Salient region algorithm owns the superiority of intra-class tolerance, global score of features and automatically prominent scale selection under certain range. However, the major limitation behaves on performance, and that is what we attempt to improve. By reducing the number of pixels involved in saliency calculation, it can be accelerated. We use interest points detected by fast-Hessian, the detector of SURF, as the candidate feature for saliency operation, rather than the whole set in image. This implementation is thereby called Saliency based Optimization over SURF (SOSU for short). Experiment shows that bringing in of such a fast detector significantly speeds up the algorithm. Meanwhile, Robustness of intra-class diversity ensures object recognition accuracy.
收录类别: Ei
语种: 英语
卷号: 8193
文章类型: 会议论文
内容类型: 会议论文
URI标识: http://ir.ioe.ac.cn/handle/181551/7761
Appears in Collections:自适应光学技术研究室(八室)_会议论文

Files in This Item:
File Name/ File Size Content Type Version Access License
2011-08-013.pdf(719KB)会议论文--限制开放View 联系获取全文

作者单位: 中国科学院光电技术研究所

Recommended Citation:
Deng Li,Wang Chunhong,Rao Changhui. Discriminative region extraction and feature selection based on the combination of SURF and saliency[C]. 见:Proceedings of SPIE - The International Society for Optical Engineering, v 8193, 2011, International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Infrared Imaging and Applications. 2011.
Service
Recommend this item
Sava as my favorate item
Show this item's statistics
Export Endnote File
Google Scholar
Similar articles in Google Scholar
[Deng Li]'s Articles
[Wang Chunhong]'s Articles
[Rao Changhui]'s Articles
CSDL cross search
Similar articles in CSDL Cross Search
[Deng Li]‘s Articles
[Wang Chunhong]‘s Articles
[Rao Changhui]‘s Articles
Related Copyright Policies
Null
Social Bookmarking
Add to CiteULike Add to Connotea Add to Del.icio.us Add to Digg Add to Reddit
文件名: 2011-08-013.pdf
格式: Adobe PDF
所有评论 (0)
暂无评论
 
评注功能仅针对注册用户开放,请您登录
您对该条目有什么异议,请填写以下表单,管理员会尽快联系您。
内 容:
Email:  *
单位:
验证码:   刷新
您在IR的使用过程中有什么好的想法或者建议可以反馈给我们。
标 题:
 *
内 容:
Email:  *
验证码:   刷新

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

 

 

Valid XHTML 1.0!
Copyright © 2007-2016  中国科学院光电技术研究所 - Feedback
Powered by CSpace