基于节点平衡模型的视频概念分析中的线性多模态融合

Jie Geng, Z. Miao, Qinghua Liang, Shu Wang
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引用次数: 0

摘要

在基于内容的视频概念分析中,颜色、纹理、形状、运动等多种形态需要分别分析,融合在一起才能得到综合的结果。提出了一种基于力学节点平衡模型的多模态融合方法。它将多模式评分和融合评分作为物理节点。在这些节点之间,我们定义相关性,将其视为将节点移动到新位置的力。最后,整个节点系统将处于一个平衡状态,作为融合的结果。该方法本质上是一个具有线性融合方程的线性融合模型。通过期望最大(EM)算法对相关性进行优化,该算法只需几次迭代,效率很高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Linear multimodal fusion in video concept analysis based on node equilibrium model
Multiple modalities such as color, texture, shape and motion need to be analyzed separately and fused together to get the comprehensive result in content-based video concept analysis. We propose a multimodal fusion method based on a mechanical node equilibrium model. It treats the scores ofmultiple modalities and the fused score as physical nodes. Between these nodes, we define correlations which are treated as forces to move the nodes to a new position. Finally, the whole node system will be at an equilibrium status which is regarded as the fusion result. Essentially, the proposed method is a linear fusion model with linear fusion equations. The correlations are optimized by an expectation maximum (EM) algorithm which is quite efficient needing only several iterations.
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