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2015
Springer

Orderless and Blurred Visual Tracking via Spatio-temporal Context

3 years 9 months ago
Orderless and Blurred Visual Tracking via Spatio-temporal Context
In this paper,a novel and robust method which exploits the spatio-temporal context for orderless and blurred visual tracking is presented.This lets the tracker adapt to both rigid and deformable objects on-line even if the image is blurred.We observe that a RGB vectorof animage which is resizedinto a small fixed size can keep enough useful information.Based on this observation and computational reasons,we propose to resize the windows ofboth template and candidate target images into 2 × 2 and use Euclidean Distance to compute the similarity between these two RGB imagevectors for the preliminary screening.We then apply spatio-temporal context based on Bayesian framework to further compute a confidence map for obtaining the best target location.Experimental results on challenging video sequences in MATLAB without code optimization show the proposed tracking method outperforms eightstate-of-the-art methods.
Manna Dai, Peijie Lin, Lijun Wu, Zhicong Chen, Son
Added 14 Apr 2016
Updated 14 Apr 2016
Type Journal
Year 2015
Where MMM
Authors Manna Dai, Peijie Lin, Lijun Wu, Zhicong Chen, Songlin Lai, Jie Zhang, Shuying Cheng, Xiangjian He
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