[1]卞 乐,李天峰,韦 怡,等.HLBP与颜色特征自适应融合的粒子滤波目标跟踪改进算法[J].南京师范大学学报(工程技术版),2018,18(01):056.[doi:10.3969/j.issn.1672-1292.2018.01.008]
 Bian Le,Li Tianfeng,Wei Yi,et al.Improved Particle Filtering Target Tracking Algorithm forHLBP and Color Feature Adaptive Fusion[J].Journal of Nanjing Normal University(Engineering and Technology),2018,18(01):056.[doi:10.3969/j.issn.1672-1292.2018.01.008]
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HLBP与颜色特征自适应融合的粒子滤波目标跟踪改进算法
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南京师范大学学报(工程技术版)[ISSN:1006-6977/CN:61-1281/TN]

卷:
18卷
期数:
2018年01期
页码:
056
栏目:
计算机工程
出版日期:
2018-03-31

文章信息/Info

Title:
Improved Particle Filtering Target Tracking Algorithm forHLBP and Color Feature Adaptive Fusion
文章编号:
1672-1292(2018)01-0056-08
作者:
卞 乐李天峰韦 怡曾毓敏
南京师范大学物理科学与技术学院,江苏 南京 210023
Author(s):
Bian LeLi TianfengWei YiZeng Yumin
School of Physics Science and Technology,Nanjing Normal University,Nanjing 210023,China
关键词:
粒子滤波HLBP纹理特征颜色特征自适应权值
Keywords:
particle filterHLBP texture featurecolor featureadaptive weights
分类号:
TP391
DOI:
10.3969/j.issn.1672-1292.2018.01.008
文献标志码:
A
摘要:
针对只采用颜色特征的经典粒子滤波目标跟踪算法无法适用相同颜色干扰情况的缺陷,提出一种结合HLBP特征与颜色特征的自适应粒子滤波跟踪算法. 该算法采用Haar型局部二值模式算子(Haar local binary pattern,HLBP)提取的HLBP纹理特征与颜色特征结合,通过自适应权值动态调整颜色特征和纹理特征在追踪过程中的比重,实现颜色纹理特征的自适应融合. 实验表明,该算法改进了相同颜色干扰情况下的追踪效果,并在目标被遮挡的情况下仍能持续稳定地追踪,提高了追踪的准确度和适用性.
Abstract:
In this paper,an adaptive particle filter tracking algorithm combining HLBP feature and color feature is proposed. This algorithm is based on imperfection of the classical particle filter target tracking algorithm:it only uses the color feature to track and does not perform effectively in the same color interference condition. Our algorithm uses the Haar local binary model operator to extract the HLBP texture feature and combine it with the color feature. Through the opposed model,we dynamically adjust adaptive weights of the color characteristics and texture features in the tracking process,which achieve the adaptive fusion between the color feature and texture feature. Experiments show that the tracking result is greatly strengthened under the same color interference with our algorithm. What’s more,in case of occlusions, our algorithm can still track stably and continuously,thus improving the accuracy and applicability of tracking.

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相似文献/References:

[1]夏瑜,吴小俊.基于新颖相似度的视觉跟踪算法[J].南京师范大学学报(工程技术版),2008,08(04):068.
 Xia Yu,Wu Xiaojun.Visual Tracking Algorithm Based on a Novel Similarity Function[J].Journal of Nanjing Normal University(Engineering and Technology),2008,08(01):068.

备注/Memo

备注/Memo:
收稿日期:2017-11-01.
基金项目:江苏省科技支撑计划(BE2014139)、江苏省基础研究计划(自然科学基金)——青年基金项目(BK20171031).
通讯联系人:曾毓敏,博士,教授,研究方向:语音和图像处理. E-mail:zengyumin@njnu.edu.cn
更新日期/Last Update: 1900-01-01