NDLI: Correlation-guided multi-object tracking with correlation feature transfer

Content Provider	IET Digital Library
Author	Li, Jiatong Zhao, Yanjie Jiang, Zhiguo
Abstract	Here, the authors propose a correlation-guided Monte Carlo Markov chain (MCMC) solver to promote the efficiency for tracking multiple objects under recursive Bayesian filtering framework. Instead of randomly proposing the target location according to certain distribution, the authors’ method guides the MCMC solver to sample among locations that the targets are more likely to appear. The high possible locations for each target are obtained using its corresponding response map by evaluating the correlation between the target appearance and its online model. Furthermore, the proposed tracking framework is natural to transfer the rich domain-specific offline correlation features into the target online model. With the calculation in the Fourier domain and the reversible jump strategy for MCMC, the correlation-guided method is able to track variable multiple objects with high efficiency. At the same time, the correlation feature transfer strategy is capable of improving tracking precision with easy offline training. The proposed method is evaluated by both the synthetic and real scenario videos. The experimental results demonstrate the effectiveness of the proposed method and its superior performance against its counterparts.
Starting Page	139
Ending Page	145
Page Count	7
ISSN	17519632
Volume Number	13
e-ISSN	17519640
Issue Number	Issue 2, Mar (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cvi/13/2
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cvi.2018.5011
Journal	IET Computer Vision
Publisher Date	2018-09-06
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Bayes Method Computer Vision And Image Processing Technique Correlation Feature Transfer Strategy Correlation Method Correlation-guided Method Correlation-guided Monte Carlo Markov Chain Solver Correlation-guided Multiobject Tracking Domain-specific Offline Correlation Features Filtering Method in Signal Processing Filtering Theory Markov Processes MCMC Solver Monte Carlo Method Object Detection Object Tracking Online Model Optical, Image And Video Signal Processing Recursive Bayesian Filtering Framework Recursive Filter Response Map Target Appearance Tracking Framework Tracking Precision Variable Multiple Objects Video Signal Processing
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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