Fast view-based 3D model retrieval via unsupervised multiple feature fusion and online projection learning
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- 作者：Jun Xiao junx@zjuem.zju.edu.cn" class="auth_mail" title="E-mail the corresponding author ; Yinfu Feng ; yinfufeng@zju.edu.com" class="auth_mail" title="E-mail the corresponding author ; Mingming Ji mjcs@zju.edu.cn" class="auth_mail" title="E-mail the corresponding author ; Yueting Zhuang yzhuang@zju.edu.cn" class="auth_mail" title="E-mail the corresponding author
- 关键词：View-based 3D model retrieval ; Multiple feature fusion ; Online projection learning ; Out-of-sample
- 刊名：Signal Processing
- 出版年：2016
- 出版时间：March 2016
- 年：2016
- 卷：120
- 期：Complete
- 页码：702-713
- 全文大小：1548 K
文摘
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An Unsupervised Multiple Feature Fusion (UMFF) algorithm is proposed to fuse multiple features for 3D model representation.
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The ℓ1-graph method is used to learn roust and datum-adaptive graph to preserve local geometric structure information.
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An efficient Online Projection Learning (OPL) algorithm is designed to solve the out-of-sample problem.