计算机应用与软件Issue(12)：298-302,5.DOI:10.3969/j.issn.1000-386x.2014.12.073
基于 SIFT 特征和模板更新的粒子滤波目标跟踪算法
PARTICLE FILTER OBJECT TRACKING ALGORITHM BASED ON SIFT FEATURES AND MODEL UPDATE
曹正洁 1王汇源 1张元元 2江二华1
作者信息
- 1. 山东大学信息科学与工程学院 山东 济南 250100
- 2. 山东省科学院情报研究所 山东 济南250000
- 折叠
摘要
Abstract
In traditional particle filter algorithm, the weight of each particle is updated only by the colour feature of the object, which may easily lead to error tracking when the object and the background have similar colour distribution or the object is occluded.Scale-invariant features are highly discriminative, but to use SIFT only is insufficient to describe small targets.A new method is proposed in this paper to handle with these two situations, in which the target model is built by SIFT feature and colour feature, and the particle filter is integrated to achieve object tracking.In order to avoid error updating of the target model, in this paper whether the colour target model is to be updated or not depends on the number of matching feature points between the tracking result in current frame and the SIFT target model.Experimental results show that the proposed method can effectively improve the tracking precision especially when the object is occluded or under clutter background with similar colours.关键词
目标跟踪/粒子滤波/尺度不变特征/模板更新Key words
Object tracking/Particle filter/Scale-invariant feature/Model update分类
信息技术与安全科学引用本文复制引用
曹正洁,王汇源,张元元,江二华..基于 SIFT 特征和模板更新的粒子滤波目标跟踪算法[J].计算机应用与软件,2014,(12):298-302,5.
