Cencen Zhong

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As standard probabilistic latent semantic analysis (pLSA) is oriented to discrete quantity only, pLSA with Gaussian mixtures (GM-pLSA) succeeding in transferring it to continuous feature space is proposed, which uses Gaussian mixture model to describe the feature distribution under each latent aspect. However, inheriting from pLSA, GM-pLSA still overlooks(More)
As an essentially multi-label classification problem, audio concept detection is normally solved by treating concepts independently. Since in this process the original useful concept correlation information is missing, this paper proposes a new model named Correlated-Aspect Gaussian Mixture Model (C-AGMM) to take advantage of such a clue for enhancing(More)
For video annotation refinement, a reasonable concept correlation representation is crucial. In this paper, we present a data-specific concept correlation estimation procedure for this task, where the resulting correlation with respect to each data encodes both its visual and high-level characteristics. Specifically, this procedure comprises two major(More)
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