中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Improved Kernel Correlation Filter Tracking with Gaussian scale space

文献类型:会议论文

作者Tan SK(谭舒昆); Liu YP(刘云鹏); Li YC(李义翠)
出版日期2016
会议名称International Symposium on Infrared Technology and Application and the International Symposiums on Robot Sensing and Advanced Control
会议日期May 9-11, 2016
会议地点Beijing
关键词visual object tracking kernel correlation filter Gaussian scale space
页码1-7
通讯作者谭舒昆
中文摘要Recently, Kernel Correlation Filter (KCF) has achieved great attention in visual tracking filed, which provide excellent tracking performance and high possessing speed. However, how to handle the scale variation is still an open problem. In this paper, focusing on this issue that a method based on Gaussian scale space is proposed. Firstly, we will use KCF to estimate the location of the target, the context region which includes the target and its surrounding background will be the image to be matched. In order to get the matching image of a Gaussian scale space, image with Gaussian kernel convolution can be got. After getting the Gaussian scale space of the image to be matched, then, according to it to estimate target image under different scales. Combine with the scale parameter of scale space, for each corresponding scale image performing bilinear interpolation operation to change the size to simulate target imaging at different scales. Finally, matching the template with different size of images with different scales, use Mean Absolute Difference (MAD) as the match criterion. After getting the optimal matching in the image with the template, we will get the best zoom ratio s, consequently estimate the target size. In the experiments, compare with CSK, KCF etc. demonstrate that the proposed method achieves high improvement in accuracy, is an efficient algorithm.
收录类别EI ; CPCI(ISTP)
产权排序1
会议录Proceedings of SPIE - The International Society for Optical Engineering
会议录出版者SPIE
会议录出版地Bellingham, WA
语种英语
ISSN号0277-786X
ISBN号978-1-5106-0772-9
WOS记录号WOS:000391228600103
源URL[http://ir.sia.cn/handle/173321/19160]  
专题沈阳自动化研究所_光电信息技术研究室
推荐引用方式
GB/T 7714
Tan SK,Liu YP,Li YC. Improved Kernel Correlation Filter Tracking with Gaussian scale space[C]. 见:International Symposium on Infrared Technology and Application and the International Symposiums on Robot Sensing and Advanced Control. Beijing. May 9-11, 2016.

入库方式: OAI收割

来源:沈阳自动化研究所

浏览0
下载0
收藏0
其他版本

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。