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Sketch retrieval and relevance feedback with biased SVM classification

机译:具有偏向SVM分类的草图检索和相关性反馈

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摘要

This paper proposes an effective approach for content-based sketch retrieval. It addresses three characteristics as follows. Firstly, both structural relations and global shape descriptors are combined to represent sketch content. Secondly, feature weighting and combination are performed to obtain a reasonable mechanism for similarity calculation. Finally, relevance feedback based on biased SVM (BSVM) algorithm is employed to capture user's query interests online and thus improve retrieval performance. Experiments prove the effectiveness of our proposed method in sketch retrieval.
机译:本文提出了一种有效的基于内容的草图检索方法。它解决了以下三个特征。首先,将结构关系和整体形状描述符组合起来以表示草图内容。其次,进行特征加权和组合以获得合理的相似度计算机制。最后,基于偏向支持向量机(BSVM)算法的相关反馈被用于在线捕获用户的查询兴趣,从而提高检索性能。实验证明了我们提出的方法在草图检索中的有效性。

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