[1]韩华,丁永生,郝矿荣.综合颜色和小波纹理特征的免疫粒子滤波视觉跟踪[J].智能系统学报,2011,6(04):289-294.
 HAN Hua,DING Yongsheng,HAO Kuangrong.An immune particle filter video tracking method based on color and wavelet texture[J].CAAI Transactions on Intelligent Systems,2011,6(04):289-294.
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综合颜色和小波纹理特征的免疫粒子滤波视觉跟踪(/HTML)
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第6卷
期数:
2011年04期
页码:
289-294
栏目:
出版日期:
2011-08-25

文章信息/Info

Title:
An immune particle filter video tracking method based on color and wavelet texture
文章编号:
1673-4785(2011)04-0289-06
作者:
韩华1丁永生12郝矿荣12
1.东华大学 信息科学与技术学院,上海 201620;
2. 数字化纺织服装技术教育部 工程研究中心,上海 201620
Author(s):
HAN Hua1 DING Yongsheng12 HAO Kuangrong12
1. College of Information Sciences and Technology, Donghua University, Shanghai 201620, China;
2.Engineering Research Center of Digitized Textile & Fashion Technology, Ministry of Education, Shanghai 201620, China
关键词:
粒子滤波免疫粒子滤波小波纹理特征相似性度量视觉跟踪
Keywords:
particle filter immune particle filter wavelet texture similarity measurement
分类号:
TP277
文献标志码:
A
摘要:
针对标准粒子滤波视觉跟踪时的缺陷,尤其是其“样贫”和目标特征不明显等问题,提出了结合小波纹理特征的免疫粒子滤波算法.小波纹理特征的加入,使得单纯依靠颜色特征不能很好适应环境变化的情况得到了改善.同时通过加入免疫优化算法,提高了粒子的多样性,尤其是在发生遮挡时减少了“样贫”的影响.通过实验验证了所提算法的有效性和鲁棒性.与基于单一特征的跟踪方法相比,该算法能稳健地实现对复杂场景下目标的跟踪.
Abstract:
Focusing on the drawbacks of standard particle filters in visual tracking, a new immune particle filter was proposed based on color and wavelet texture feature to avoid “sample impoverishment” and incomplete feature. Since the wavelet feature was added, the poor performance of only one feature was improved when the environment changed. In addition, the proposed immune optimization algorithm improved the diversity of particles, especially the decline of the impact of sample impoverishment when occlusion occurs. At last, the effectiveness and robustness of the proposed method was verified by experiments. In contrast to the single feature tracking method, the proposed method can track targets with complex backgrounds more steadily.

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备注/Memo

备注/Memo:
收稿日期: 2010-12-08.
基金项目:国家自然科学基金重点资助项目(61134009);国家自然科学基金资助项目(60975059,60775052);国家ITER计划国内配套研究资助项目(2010GB108004);教育部高等学校博士学科点专项科研基金资助项目(20090075110002);上海市优秀学术带头人计划资助项目(11XD1400100);上海市科学技术委员会重点基础研究资助项目(10JC1400200, 09JC1400900);上海市科学技术委员会技术标准专项资助项目(10DZ0506500).
通信作者:丁永生.E-mail:ysding@dhu.edu.cn.
作者简介:
韩华,女,1983年生,博士研究生,主要研究方向为智能视频处理.
丁永生,男,1967年生,教授,博士生导师,主要研究方向为智能系统、网络智能、DNA计算、人工免疫系统、生物网络结构、智能机器人、生物信息学、数字化纺织服装、智能决策与分析等.
郝矿荣,女,1964年生,教授,博士生导师,主要研究方向为机器视觉、模式识别、智能机器人、智能控制等.
更新日期/Last Update: 2011-09-30