Joint Alignment and Clustering via Low-Rank Representation | |
Qi Li![]() ![]() | |
2013-11 | |
会议日期 | 2013年11月5-8日 |
会议地点 | Naha, Japan |
关键词 | Joint Alignment And Clustering Low-rank Representation Augmented Lagrange Multiplier Method |
英文摘要 |
Both image alignment and image clustering are widely researched with numerous applications in recent years. These two problems are traditionally studied separately. However in many real world applications, both alignment and clustering results are needed. Recent study has shown that alignment and clustering are two highly coupled problems. Thus we try to solve the two problems in a unified framework. In this paper, we propose a novel joint alignment and clustering algorithm by integrating spatial transformation parameters and clustering parameters into a unified objective function. The proposed function seeks the lowest rank representation among all the candidates that can represent misaligned images. It is indeed a transformed Low-Rank Representation. As far as we know, this is the first time to cluster the misaligned images using the transformed Low-Rank Representation. We can solve the proposed function by linearizing the objective function, and then iteratively solving a sequence of linear problems via the Augmented Lagrange Multipliers method. Experimental results on various data sets validate the effectiveness of our method. |
会议录 | Asian Conference on Pattern Recognition
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内容类型 | 会议论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/11678] ![]() |
专题 | 自动化研究所_智能感知与计算研究中心 |
通讯作者 | Li, Qi |
作者单位 | Center for Research on Intelligent Perception and Computing, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China |
推荐引用方式 GB/T 7714 | Qi Li,Zhenan Sun,Ran He,et al. Joint Alignment and Clustering via Low-Rank Representation[C]. 见:. Naha, Japan. 2013年11月5-8日. |
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