caa a22 4500 60544725X CHVBK 20210128100131.0 cr unu---uuuuu 210128e20150701xx s 000 0 eng 10.1007/s11042-013-1850-9 doi (NATIONALLICENCE)springer-10.1007/s11042-013-1850-9 3D CAD model retrieval based on the combination of features [Elektronische Daten] [Qiang Chen, Bin Fang, Yong-Mei Yu, Yan Tang] To improve the retrieval performance of 3D CAD model, we propose three combined feature descriptor and a class information based feature descriptor. First, we propose a novel feature descriptor Normal Angle Area (NAA) based on the 3D models surface and normals, and then we combined NAA with D2 and Bounding Box feature to form a more powerful feature DBNAA. Second, we combine DBNAA with Depth buffer images (DE), Ray extent (RE) to form DBNAA_DERE descriptor, and combine DBNAA with PANORAMA to form DBNAA_PANORAMA descriptor. Finally, we utilize the class information of dataset and propose a method called DBNAA_CBR which use a novel method to fuse class information into retrieval process. Experimental results on ESB dataset show that the results of DBNAA is similar to light field descriptors (LF) but with lower computational cost, DBNAA_DERE is better than DESIRE, DBNAA_PANORAMA performed better than all other non class information based methods. Further experiments showed that when we set an appropriate parameter for DBNAA_CBR it performs better than CBR-ZFDR. Springer Science+Business Media New York, 2014 Feature combination nationallicence 3D CAD model retrieval nationallicence Depth buffer image nationallicence Ray extent nationallicence Class information nationallicence Normal angle area nationallicence Chen Qiang School of Computer Science, Chongqing University, 400030, Chongqing, China aut Fang Bin School of Computer Science, Chongqing University, 400030, Chongqing, China aut Yu Yong-Mei College of Computer and Information Science, Southwest University, 400715, Chongqing, China aut Tang Yan College of Computer and Information Science, Southwest University, 400715, Chongqing, China aut Multimedia Tools and Applications Springer US; http://www.springer-ny.com 74/13(2015-07-01), 4907-4925 1380-7501 74:13<4907 2015 74 11042 https://doi.org/10.1007/s11042-013-1850-9 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s11042-013-1850-9 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Chen Qiang School of Computer Science, Chongqing University, 400030, Chongqing, China aut NATIONALLICENCE 700 1- Fang Bin School of Computer Science, Chongqing University, 400030, Chongqing, China aut NATIONALLICENCE 700 1- Yu Yong-Mei College of Computer and Information Science, Southwest University, 400715, Chongqing, China aut NATIONALLICENCE 700 1- Tang Yan College of Computer and Information Science, Southwest University, 400715, Chongqing, China aut NATIONALLICENCE 773 0- Multimedia Tools and Applications Springer US; http://www.springer-ny.com 74/13(2015-07-01), 4907-4925 1380-7501 74:13<4907 2015 74 11042