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Probabilistic-Based Image Categorization Using Novel Visual Vocabulary

机译:使用新型视觉词汇的基于概率的图像分类

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The visual words representation is widely applied to many multimedia applications. In this paper, we use a novel visual vocabulary developed in our previous work and propose a category-specific visual model for image categorization. The category-specific visual model is composed by macro and micro visual words description, respectively. We can categorize image by considering macro or micro content in a flexible way. Meanwhile, we will propose a probabilistic-based method to achieve effective and excellent image categorization. The performance evaluation for the proposed systems indicates that the new categorization scheme achieves promising results.
机译:视觉单词表示已广泛应用于许多多媒体应用程序。在本文中,我们使用先前工作中开发的新颖视觉词汇,并提出了用于图像分类的特定类别视觉模型。类别特定的视觉模型分别由宏观和微观视觉词描述组成。我们可以通过灵活考虑宏观或微观内容来对图像进行分类。同时,我们将提出一种基于概率的方法来实现有效和出色的图像分类。对所提出系统的性能评估表明,新的分类方案取得了可喜的结果。

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