计算机工程与应用2016，Vol.52Issue(1)：120-126,265,8.DOI:10.3778/j.issn.1002-8331.1312-0463
基于约束知识的IP-MCMC-PF目标跟踪方法研究
Research on target tracking based on constraint knowl-edge IP-MCMC-PF
摘要
Abstract
Particle filter algorithm for target tracking with interference may occur in the problem such as lower particle diversity and reduced precision. In allusion to this instance, a novel tracking method based on constraint knowledge is pro-posed. This method improves the precision of the particle prediction using constraint knowledge. The problem of the particle degeneration is effectively solved by improving the particle diversity with the parallel IP-MCMC method. On this basis, the proposed method realizes the online study algorithm using PN learning, which is used to update the sample distribution of particles and the training samples of the detector. The accuracy and adaptability of the tracking method under complex background is effectively improved. Experimental results show that the proposed method has good effect under the situa-tion of various interference(e.g., shade, deformation, illumination change).关键词
粒子滤波/约束知识/IP-MCMC抽样/PN学习Key words
particle filter/constraint knowledge/IP-MCMC sampling/PN learning分类
信息技术与安全科学引用本文复制引用
梁启香,汪荣贵,张冬梅,李想,秦飞..基于约束知识的IP-MCMC-PF目标跟踪方法研究[J].计算机工程与应用,2016,52(1):120-126,265,8.基金项目
国家自然科学基金(No.61075032) （No.61075032）
中央高校基本科研业务费专项资金(No.2012HGCX0001). （No.2012HGCX0001）
