计算机工程2017，Vol.43Issue(1)：253-258,6.DOI:10.3969/j.issn.1000-3428.2017.01.044
基于背景差分检测和改进GM-PHD滤波器的多目标跟踪
Multiple Object Tracking Based on Background Subtraction Detection and Improved GM-PHD Filter
摘要
Abstract
Target label confusion and loss are usually caused by occlusion and detection missing in multiple object tracking process,which leads to failing tracking.Aiming at this problem,an improved tracking method based on Gaussian Mixture Probability Hypothesis Density(GM-PHD) filter is proposed.The binary image mapping and testing sets are got by Background Subtraction Detection(BSD),and the object appearance is detected by detector based on the appearance.The two testing sets got by background subtraction and appearance detector are fused.The improved GM-PHD filter is used to keep the object tracking trajectory so as to deal with some uncertainty in object tracking.Experimental results show that the tracking precision of the proposed method is superior to that of GM-PHD method,color appearance method and SMC-PHD method.关键词
多目标跟踪/背景差分检测/滤波/置信概率/多目标跟踪精度Key words
multiple object tracking/Background Subtraction Detection (BSD)/filtering/confidence probability/Multiple Object Tracking Precision(MOTP)分类
信息技术与安全科学引用本文复制引用
谌湘倩,马绍惠,须文波..基于背景差分检测和改进GM-PHD滤波器的多目标跟踪[J].计算机工程,2017,43(1):253-258,6.基金项目
河南省教育厅科学技术研究重点项目(14A520046) （14A520046）
河南省高等学校重点科研项目(15B520006). （15B520006）
