作者
Paul Brasnett, Lyudmila Mihaylova, David Bull, Nishan Canagarajah
发表日期
2007/8/1
期刊
Image and vision computing
卷号
25
期号
8
页码范围
1217-1227
出版商
Elsevier
简介
This paper presents visual cues for object tracking in video sequences using particle filtering. A consistent histogram-based framework is developed for the analysis of colour, edge and texture cues. The visual models for the cues are learnt from the first frame and the tracking can be carried out using one or more of the cues. A method for online estimation of the noise parameters of the visual models is presented along with a method for adaptively weighting the cues when multiple models are used. A particle filter (PF) is designed for object tracking based on multiple cues with adaptive parameters. Its performance is investigated and evaluated with synthetic and natural sequences and compared with the mean-shift tracker. We show that tracking with multiple weighted cues provides more reliable performance than single cue tracking.
引用总数
学术搜索中的文章
P Brasnett, L Mihaylova, D Bull, N Canagarajah - Image and vision computing, 2007