Hanhe Lin

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in this paper, we focus on the problem of predicting sensitive relationships from Email corpus. We refer to the problem of predicting sensitive relationships from a social network as link re-identification. We propose a predicting sensitive relationships method which has two steps. First step is counting mutual privacy communication. Second step is(More)
We propose a novel, online adaptive one-class support vector machines algorithm for anomaly detection in crowd scenes. Integrating incremental and decremental one-class support vector machines with a sliding buffer offers an efficient and effective scheme, which not only updates the model in an online fashion with low computational cost, but also discards(More)
Detecting abnormal events in video surveillance is a challenging problem due to the large scale, stream fashion video data as well as the real-time constraint. In this paper, we present an online, adaptive, and real-time framework to address this problem. The spatial locations in a frame is partitioned into grids, in each grid the proposed Adaptive(More)
Crowd scene analysis has caught significant attention both in academia and industry as it has a great number of potential applications. In this paper, we propose a novel spatial-temporal pyramid matching scheme for crowd scene analysis. Video segments are represented as concatenated histograms of all cells at all pyramid levels with corresponding weights,(More)
Using video manifold to analyze video scenes and detect possible anomaly has become a popular research topic in recent years. While a number of attempts have been proposed and reported promising outcomes, there is currently a lack of understanding about the parameter setting for various components in the algorithmic framework. In this paper we look at some(More)
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