南通大学学报（自然科学版）2018，Vol.17Issue(3)：6-11,6.
无人机视角下的特征匹配引导粒子滤波跟踪算法
Features Matching Guided Particle Filter Tracking Algorithm Based on the Drone
摘要
Abstract
Particle filter (PF) has been widely applied to visual object tracking. However, due to the simultaneous movement of the camera and the detected object, the traditional PF tracking algorithm for the fixed camera is disabled. Aiming at this problem, this paper proposes an improved PF algorithm: features matching guided particle filtering algorithm (FMG-PF), which can effectively track the targets. Firstly, scale invariant feature transform (SIFT) features matching result is used as initial localization. Then it is corrected by combination of spatial weighted HOG feature and particle filter frame as tracking result. Finally, chamfer distance is employed to modify the feature points of tracked target and the revised target feature points are used as the features template for the next frame matching.Experiments show that the proposed algorithm is able to track the road traffic targets effectively.关键词
特征匹配引导/粒子滤波/无人机/目标跟踪Key words
features matching guided/particle filter/drone/target tracking分类
信息技术与安全科学引用本文复制引用
阚雨婷,施佺,王晗..无人机视角下的特征匹配引导粒子滤波跟踪算法[J].南通大学学报（自然科学版）,2018,17(3):6-11,6.基金项目
国家自然科学基金项目 (61872425) （61872425）
江苏省高校自然科学基金项目 (17KJB520029) （17KJB520029）
南通市工业创新项目 (GY12016020) （GY12016020）
