Fuzzy Approach for Semantic Face Image Retrieval
Fuzzy Approach for Semantic Face Image Retrieval
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DOI：
10.1093/comjnl/bxs041
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发表时间：
2012-09
期刊：
影响因子：
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通讯作者：
P. Conilione;Dianhui Wang
中科院分区：
文献类型：
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作者：
P. Conilione;Dianhui Wang
我们的目标是实现语义人脸图像检索（FIR）之间的语义鸿沟的低层视觉特征的图像和高层次的标签描述的面部特征。这允许用户基于面部特征的描述而不是示例图像来检索面部图像。我们的方法的语义差距问题，通过开发一个基于模糊的方法，找到一个映射之间的低级别的功能和词汇，描述了面部特征的语义。本文的贡献是一种新的方法，使用模糊聚类和模糊推理方法来获得一个新的图像的每个语义标签的隶属度。实验结果表明，该方法具有良好的图像标注效果，并为基于局部人脸特征的FIR系统提供了良好的基础。我们在网上提供了一个演示系统。此外，我们的系统不是特定领域的，可以推广和应用到图像检索领域的其他问题。
Our aim is to realize semantic face image retrieval (FIR)\ by bridging the semantic-gap between low-level visual features of images and the high-level labels that describe facial features. This allows a user to retrieve face images based on a description of face features rather than an example image. We approach the semantic-gap problem by developing a fuzzy-based method of finding a mapping between the low-level features and the vocabulary that describes the semantics of the face features. The contribution of this paper is a new method of using fuzzy clustering and fuzzy inference methods to derive the degree of membership for each semantic label to a new image. Our experiments show that our approach has good results for annotating images, and provides a sound foundation for local face feature-based FIR systems. We have made available a demonstration system online. Further, our system is not domain specific and can be generalized and applied to other problems in the field of image retrieval.