激光与光电子学进展, 2020, 57 (22): 221012, 网络出版: 2020-11-12
基于多视角低秩表征的短视频多标签学习模型 下载: 878次
Microvideo Multilabel Learning Model Based on Multiview Low-Rank Representation
图像处理 低秩表征 多标签学习 多视角学习 短视频 image processing low-rank representation multi-label learning multi view learning micro-video
摘要
提出一种基于多视角低秩表征的短视频多标签分类模型。该模型将低秩表征和多标签学习结合到同一框架中,利用不同类型特征的一致性学习本征稳定的低秩表示。同时为了获得标签相关性的潜在表示,构建了标签相关性学习项来自适应地捕获标签的相关性矩阵。此外,模型利用监督信息进一步提高了其表征能力。大量的实验结果证实了所提方法的优越性。
Abstract
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.
吕卫, 李德盛, 谭浪, 井佩光, 苏育挺. 基于多视角低秩表征的短视频多标签学习模型[J]. 激光与光电子学进展, 2020, 57(22): 221012. 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.