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Supervised by Ministry of Industry and Information Technology of The People''s Republic of China Sponsored by Harbin Institute of Technology Editor-in-chief Yu Zhou ISSNISSN 1005-9113 CNCN 23-1378/T

Related citation:Lin Lin,Xiao-Long Xie,Fang-Yu Chen.3D Model Retrieval Method Based on Affinity Propagation Clustering[J].Journal of Harbin Institute Of Technology(New Series),2013,20(3):12-21.DOI:10.11916/j.issn.1005-9113.2013.03.003.
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3D Model Retrieval Method Based on Affinity Propagation Clustering
Author NameAffiliationE-mail
Lin Lin School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, China 
Xiao-Long Xie School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, China  
Fang-Yu Chen School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, China  
In order to improve the accuracy and efficiency of 3D model retrieval, the method based on affinity propagation clustering algorithm is proposed. Firstly, projection ray-based method is proposed to improve the feature extraction efficiency of 3D models. Based on the relationship between model and its projection, the intersection in 3D space is transformed into intersection in 2D space, which reduces the number of intersection and improves the efficiency of the extraction algorithm. In feature extraction, multi-layer spheres method is analyzed. The two-layer spheres method makes the feature vector more accurate and improves retrieval precision. Secondly, Semi-supervised Affinity Propagation (S-AP) clustering is utilized because it can be applied to different cluster structures. The S-AP algorithm is adopted to find the center models and then the center model collection is built. During retrieval process, the collection is utilized to classify the query model into corresponding model base and then the most similar model is retrieved in the model base. Finally, 75 sample models from Princeton library are selected to do the experiment and then 36 models are used for retrieval test. The results validate that the proposed method outperforms the original method and the retrieval precision and recall ratios are improved effectively.
Key words:  feature extraction  project ray-based method  affinity propagation clustering  3D model retrieval