Title :
SHREC’08 entry: Training set expansion via autotags
Author :
Goldfeder, C. ; Haoyun Feng ; Allen, Peter
Author_Institution :
Columbia Univ., New York, NY
Abstract :
Training a 3D model classifier on a small dataset is very challenging. However, large datasets of partially classified models are now commonly available online. We use an external training set of models with associated text tags to automatically assign tags to both training and query models. The similarity between these tags, used in conjunction with a standard shape descriptor, yields a multiclassifier that outperforms the standalone shape descriptor.
Keywords :
classification; indexing; query processing; text analysis; 3D model classifier; SHREC; autotag; partially classified model; query model; shape descriptor; tag assignment; tag similarity; text tag; training set expansion; Aircraft; Content based retrieval; Information analysis; Information retrieval; Nearest neighbor searches; Solid modeling; Classification; H.3.1 [Information Storage and Retrieval]: Content Analysis and Indexing; autotagging; labeling;
Conference_Titel :
Shape Modeling and Applications, 2008. SMI 2008. IEEE International Conference on
Conference_Location :
Stony Brook, NY
Print_ISBN :
978-1-4244-2260-9
DOI :
10.1109/SMI.2008.4547983