Feature Correspondence Based on Directed Structural Model Matching
Yang X(杨旭); Qiao, Hong; Liu, Zhiyong; Zhi-Yong Liu
Source PublicationImage and Vision Computing
2015
Issue33Pages:57-67
AbstractFeature correspondence lays the foundation for many tasks in computer vision and pattern recognition. In this paper the directed structural model is utilized to represent the feature set, and the correspondence problem is then formulated as the structural model matching. Compared with the undirected structural model, the proposed directed model provides more discriminating ability and invariance against rotation and scale transformations. Finally, the recently proposed convex–concave relaxation procedure (CCRP) is generalized to approximately solve the problem. Extensive experiments on synthetic and real data witness the effectiveness of the proposed method.
KeywordGraph Matching Directed Structural Model Feature Correspondence
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/12475
Collection复杂系统管理与控制国家重点实验室_机器人理论与应用
Corresponding AuthorZhi-Yong Liu
Affiliation中国科学院自动化研究所
First Author Affilication中国科学院自动化研究所
Recommended Citation
GB/T 7714
Yang X,Qiao, Hong,Liu, Zhiyong,et al. Feature Correspondence Based on Directed Structural Model Matching[J]. Image and Vision Computing,2015(33):57-67.
APA Yang X,Qiao, Hong,Liu, Zhiyong,&Zhi-Yong Liu.(2015).Feature Correspondence Based on Directed Structural Model Matching.Image and Vision Computing(33),57-67.
MLA Yang X,et al."Feature Correspondence Based on Directed Structural Model Matching".Image and Vision Computing .33(2015):57-67.
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