Jianlou Si

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Person re-identification is still a challenging task due to large visual appearance variations caused by illumination, background, viewpoints and poses in multi-camera surveillance. To address these challenges, many methods have been proposed. In this paper, we present an efficient method, called Region-of-Interest based Features (ROIF), via combining(More)
Person re-identification (Re-ID) across non-overlapping camera views is one of the challenging problems in surveillance video analysis. In this paper, we propose to combine multiple statistical features via explicit kernel feature mapping, and learn a linear metric model by local fisher discriminant analysis (LFDA) for person Re-ID. To strengthen the(More)
Metric learning plays a critical role in person re-identification problem. Unfortunately, due to the small size of training data, the metric learning used in this scenario suffers from over-fitting which leads to degenerated performance. In this paper, we investigate the effect of regularization in metric learning for person re-identification. Concretely we(More)
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