UM
Object categorization based on hierarchical learning
Xia, Tian1; Tang, Y.Y.1; Wei, Yantao2; Li, Hong2; Li, Luoqing3
2012
Conference Name21st International Conference on Pattern Recognition, ICPR 2012
Source PublicationProceedings - International Conference on Pattern Recognition
Pages1419-1422
Conference Date11 11, 2012 - 11 15, 2012
Conference PlaceTsukuba, Japan
Author of SourceInstitute of Electrical and Electronics Engineers Inc.
AbstractIn this paper we present a new method for object categorization. Firstly an image representation is obtained by the proposed hierarchical learning method consisting of alternating between local coding and maximum pooling operations, where the local coding operation induces discrimination while the image descriptor and maximum pooling operation induces invariance in hierarchical architecture. Then the obtained effective image representation is passed to a linear classifier which is suitable for large databases for object categorization. We have demonstrated that the proposed method is robust to image variations and has low sample complexity. © 2012 ICPR Org Committee.
Language英语
Fulltext Access
Document TypeConference paper
CollectionUniversity of Macau
Affiliation1.University of Macau, China;
2.Huazhong University of Science and Technology, Wuhan 430074, China;
3.Hubei University, Wuhan 430062, China
First Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Xia, Tian,Tang, Y.Y.,Wei, Yantao,et al. Object categorization based on hierarchical learning[C]//Institute of Electrical and Electronics Engineers Inc.,2012:1419-1422.
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