An improved manifold constrained ranking method applied to 3D model retrieval

被引：0

作者：

Tan, Xiaohui ^{[1
]}

Li, Na ^{[1
]}

Wang, Rui ^{[1
]}

Guo, Ruiliang ^{[2
]}

机构：

[1] College of Information Engineering, Capital Normal University, Beijing

[2] The School of Fashion Art and Engineering, Beijing Institute of Fashion and Technology, Beijing

来源：

Journal of Computational Information Systems | 2015年 / 11卷 / 12期

基金：

中国国家自然科学基金;

关键词：

3D model retrieval; Local features; Manifold ranking; Sketch search;

D O I：

10.12733/jcis14784

中图分类号：

学科分类号：

摘要：

The 3D model retrieval algorithm based on sketches is of great research value. Ranking algorithm must be used to get the most relevant models from retrieving the candidate models. However, the existing ranking algorithm based on sketch retrieval technology is unable to take the inner similarity of two line drawings. Here, an improved manifold constraints ranking algorithm is proposed by taking advantage of the inner low dimensional manifold structure in the query database. With the improved method, the precision ratio of the retrieval will be increased. The experiment results in this paper indicate that the proposed approach can provide high recall ratio of sketch retrieval. ©, 2015, Binary Information Press. All right reserved.

引用

页码：4547 / 4554

页数：7

共 27 条

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