Distance-based multiple paths quantization of vocabulary tree for object and scene retrieval

Heng Yang, Qing Wang, Ellen Yi Luen Do

科研成果: 期刊稿件文章同行评审

摘要

The state of the art in image retrieval on large scale databases is achieved by the work inspired by the text retrieval approaches. A key step of these methods is the quantization stage which maps the high-dimensional feature vectors to discriminatory visual words. This paper mainly proposes a distance-based multiple paths quantization (DMPQ) algorithm to reduce the quantization loss of the vocabulary tree based methods. In addition, a more efficient way to build a vocabulary tree is presented by using sub-vectors of features. The algorithm is evaluated on both the benchmark object recognition and the location recognition databases. The experimental results have demonstrated that the proposed algorithm can effectively improve image retrieval performance of the vocabulary tree based methods on both the databases.

源语言英语
页(从-至)253-261
页数9
期刊IPSJ Transactions on Computer Vision and Applications
2
DOI
出版状态已出版 - 2010

指纹

探究 'Distance-based multiple paths quantization of vocabulary tree for object and scene retrieval' 的科研主题。它们共同构成独一无二的指纹。

引用此