计算机工程2012，Vol.38Issue(24)：141-145,5.
基于粒子滤波的多特征融合视频行人跟踪算法
Pedestrian Tracking Algorithm in Video of Multi-feature Fusion Based on Particle Filter
摘要
Abstract
This paper presents a tracking algorithm based on multi-feature fusion in the particle filter framework to solve the problem of pedestrian tracking in onboard videos. To deal with the nonlinearity and non-Gaussianity caused by the motions of the pedestrians and the cameras in onboard videos, the particle filter tracking algorithm based on Monte-Carlo sampling is employed, the targets' states are predicted by first-order self-regression dynamic models, and the observation model is proposed to fuse four complementary features. Experimental results show that the recall of the proposed algorithm improves by more than 20% at the same precision level than the tracking algorithm without particle filter and multi-feature fusion.关键词
粒子滤波/特征融合/局部二元模式/运动平滑/扩散距离Key words
particle filter/ feature fusion/ Local Binary Pattem(LBP)/ motion smoothness/ diffusion distance分类
信息技术与安全科学引用本文复制引用
李锴,冯瑞..基于粒子滤波的多特征融合视频行人跟踪算法[J].计算机工程,2012,38(24):141-145,5.基金项目
国家"863"计划基金资助项目(2011AA100701) （2011AA100701）
上海市教育委员会科研创新基金资助项目(11CXY01) （11CXY01）
宝山区科委产学研合作基金资助项目(CXY-2010-35) （CXY-2010-35）
