DocumentCode :
2096472
Title :
Partial Relevance Feedback for 3D Model Retrieval
Author :
Baokun, Hu ; Yusheng, Liu ; Shuming, Gao ; Jing, Hu
Author_Institution :
State Key Lab. of CAD&CG, Zhejiang Univ., China
Volume :
2
fYear :
2008
fDate :
20-22 Dec. 2008
Firstpage :
198
Lastpage :
201
Abstract :
Relevance feedback (RF) proved an effect way to improve the precision and recall of 3D model retrieval. Unfortunately, through existing methods of RF, it is straightforward to find out whether a model is similar or not, but it is impossible to find out which local part is similar or not. The new partial method of RF proposed in this paper provides a good solution, in which not only the similar models are marked out but also the local parts which are similar or not are pointed out and taken advantage at the same time. This additional information contributes a lot to the improvement of 3D retrieval. Experiments show superiority in effectivity of the new method.
Keywords :
relevance feedback; 3D model retrieval; partial relevance feedback; Computer science; Feedback; Information retrieval; Kernel; Linear discriminant analysis; Radio frequency; Shape; Space technology; Wrapping; 3d model retrieval; partial relevance feedback; relevance feedback;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Computational Technology, 2008. ISCSCT '08. International Symposium on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3746-7
Type :
conf
DOI :
10.1109/ISCSCT.2008.234
Filename :
4731602
Link To Document :
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