Improving the Discriminative Power of Bag of Visual Words Model

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• 关键词：Bag of visual words ; Visual phrases ; Image retrieval
• 刊名：Lecture Notes in Computer Science
• 出版年：2017
• 出版时间：2017
• 年：2017
• 卷：10133
• 期：1
• 页码：245-256
• 丛书名：MultiMedia Modeling
• ISBN：978-3-319-51814-5
• 卷排序：10133

文摘

With the exponential increase of image database, Content Based Image Retrieval research field has started a race to always propose more effective and efficient tools to manage massive amount of data. In this paper, we focus on improving the discriminative power of the well-known bag of visual words model. To do so, we present n-BoVW, an approach that combines visual phrase model effectiveness keeping the efficiency of visual words model with a binary based compression algorithm. Experimental results on widely used datasets (UKB, INRIA Holidays, Corel1000 and PASCAL 2012) show the effectiveness of the proposed approach.