南京邮电大学学报（自然科学版）2017，Vol.37Issue(2)：38-45,8.DOI:10.14132/j.cnki.1673-5439.2017.02.007
基于轨迹关联的多目标跟踪
Multi-object tracking via trajectory association
摘要
Abstract
A novel framework to deal with the multi-object tracking algorithm is proposed.Two different association strategies are utilized to obtain global and local trajectories by the algorithm.A scene-adaptive method is firstly utilized to generate local trajectories to construct the association between new detection responses and original trajectories.Then,a novel discriminative appearance learning method is utilized to construct the association between global trajectories.Finally,a non-linear motion model is utilized to fill the gaps between trajectories,thus obtaining continuous and smooth trajectories.Experimental results on PETS 2009/2010 and TUD-Stadtmitte database demonstrate that the proposed method can achieve stable and continuous tracking trajectories under the occlusion between objects,similar appearances on different objects and direction changes of tracking objects in complex scenes.关键词
轨迹关联/场景自适应关联/增量线性判决分析/判别性表观模型/非线性运动模型Key words
trajectory association/scene-adaptive association/incremental linear discriminant analysis/discriminant apparent model/non-linear motion model分类
信息技术与安全科学引用本文复制引用
许正,朱松豪,梁志伟,徐国政..基于轨迹关联的多目标跟踪[J].南京邮电大学学报（自然科学版）,2017,37(2):38-45,8.基金项目
江苏省自然科学基金(BK20141426)、江苏省重点研发计划(BE2015701)和南京邮电大学国家自然科学基金孵化项目(NY217066)资助项目 （BK20141426）
