期刊
COGNITIVE COMPUTATION
卷 8, 期 5, 页码 839-846出版社
SPRINGER
DOI: 10.1007/s12559-016-9401-0
关键词
Common visual pattern; Feature matching; Replicator equation; Dense subgraphs
资金
- National High Technology Research and Development Program (863 Program) of China [2014AA015104]
- National Nature Science Foundation of China [61472002]
- Co-Innovation Center for Information Supply and Assurance Technology, Anhui University
- Natural Science Foundation of Anhui Province [1308085MF97]
- Natural Science Foundation of Anhui Higher Education Institution of China [KJ2015A110]
Common visual patterns discovery (CVP) is a fundamental problem in the computer vision area. It has been widely used in many computer vision tasks. Recent works have formulated this problem as a dense subgraph detection problem. Since it is NP-hard, approximate methods are required. In this paper, we propose a new method for CVP problem, called Elastic Matching (ElasticM). The main feature of the proposed ElasticM is that it uses norm constraint to induce sparse solution and thus conducts detection task naturally and more robustly in its optimization process. Promising experimental results demonstrate the benefit of the proposed CVP discovery method.
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