Caihong Yuan

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Human eye perceives an object as the entity with global information and local information. Human salience is distinctive local information in matching pedestrians across disjoint camera views, and matching on overall foreground guarantees reliable and robust identification. In this paper, we propose a strategy for the matching of mean salience to identify(More)
Generally, particle filters need a large number of particles to approximate the posterior for the purpose of ideal effect. Previous methods extract remarkable particles from the particles at time t-1 by nonlinear function. Those methods use the remarkable particles to reduce the number of particles and improve the accuracy of particle filter. However, the(More)
In this paper, we introduce a deep multi-instance learning framework to boost the instance-level person re-identification performance. Motivated by the observation of considerably dramatic and complex varieties of visual appearances in many current person re-identification datasets, we explicitly represent a deep feature representation learning method for(More)
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