Laser & Optoelectronics Progress, Volume. 57, Issue 22, 221012(2020)
Microvideo Multilabel Learning Model Based on Multiview Low-Rank Representation
We propose a microvideo multilabel learning model based on a multiview low-rank representation, which combines the low-rank representation and multilabel learning into a unified framework and uses the consistency in different features to learn an intrinsically robust low-rank representation. Meanwhile, to represent the potential label correlations, our proposed model constructs a label correlation learning term to adaptively capture the labels’ correlation matrix. Furthermore, the supervised information is exploited to further improve the representation ability of our model. Extensive experiments on a large-scale public dataset show the effectiveness of the proposed scheme.
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Wei Lü, Desheng Li, Lang Tan, Peiguang Jing, Yuting Su. Microvideo Multilabel Learning Model Based on Multiview Low-Rank Representation[J]. Laser & Optoelectronics Progress, 2020, 57(22): 221012
Category: Image Processing
Received: Mar. 10, 2020
Accepted: Apr. 10, 2020
Published Online: Nov. 12, 2020
The Author Email: Li Desheng (lidesheng1996@tju.edu.cn)