A cross-modal approach for extracting semantic relationships of concepts from an image database
A cross-modal approach for extracting semantic relationships of concepts from an image database
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DOI：
10.1109/icassp.2012.6288392
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发表时间：
2012-03
期刊：
影响因子：
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通讯作者：
Marie Katsurai;Takahiro Ogawa;M. Haseyama
中科院分区：
文献类型：
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作者：
Marie Katsurai;Takahiro Ogawa;M. Haseyama
提出了一种从图像数据库中提取概念语义关系的跨模态方法。首先，典型相关分析（CCA）被用来捕获数据库中的视觉特征和标签特征之间的跨模态相关性。然后，为了衡量概念间的关系和估计语义水平，所提出的方法侧重于图像的概率解释CCA下的分布。实验结果表明，该方法比现有的方法有很大的改进。
This paper presents a cross-modal approach for extracting semantic relationships of concepts from an image database. First, canonical correlation analysis (CCA) is used to capture the cross-modal correlations between visual features and tag features in the database. Then, in order to measure inter-concept relationships and estimate semantic levels, the proposed method focuses on the distributions of images under the probabilistic interpretation of CCA. Results of experiments conducted by using an image database showed the improvement of the proposed method over existing methods.