文章基本信息

标题：UPF Tracking Method Based on Color and SIFT Features Adaptive Fusion
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作者：Yibo Li ; Xuezheng Zhuang ; Yanmei Liu 等
期刊名称：International Journal of Signal Processing, Image Processing and Pattern Recognition
印刷版ISSN：2005-4254
出版年度：2014
卷号：7
期号：6
页码：379-390
DOI：10.14257/ijsip.2014.7.6.33
出版社：SERSC
摘要：Based on the problems that target appears rotation and noise interference in complex environment, an improved multi-feature adaptive fusion tracking method is proposed. The algorithm adopts unscented Kalman particle filter (UPF) to update the measurement information in the sample particles, better overcome the problem of the particle weight degradation. In addition, in order to overcome the defects of additive and multiplicative fusion algorithm in the feature selection, the multiple adaptive fusion characteristics method that target color distribution and scale invariance feature (SIFT) are used as complementary information. Experimental results show that the proposed method is superior to the traditional methods which are based on fixed weight or standard particle filter.
关键词：UPF; color histogram; scale invariant; adaptive fusion