Hierarchical object categorization with automatic feature selection

Islam, Saiful; Sluzek, Andrzej

doi:10.1109/imcsit.2010.5679945

Hierarchical object categorization with automatic feature selection

Proceedings of the International Multiconference on Computer Science and Information Technology, IMCSIT 2010, cilt.5, ss.45-51, 2010 (Scopus)

Yayın Türü: Makale / Özet
Cilt numarası: 5
Basım Tarihi: 2010
Doi Numarası: 10.1109/imcsit.2010.5679945
Dergi Adı: Proceedings of the International Multiconference on Computer Science and Information Technology, IMCSIT 2010
Derginin Tarandığı İndeksler: Scopus
Sayfa Sayıları: ss.45-51
TED Üniversitesi Adresli: Hayır

Özet

In this paper, we have introduced a hierarchical object categorization method with automatic feature selection. A hierarchy obtained by natural similarities and properties is learnt by automatically selected features at different levels. The categorization is a top-down process yielding multiple labels for a test object. We have tested out method and compared the experimental results with that of a nonhierarchical method. It is found that the hierarchical method improves recognition performance at the level of basic classes and reduces error at a higher level. This makes the proposed method plausible for different applications of computer vision including object categorization, semantic image retrieval, and automatic image annotation. © 2010 IEEE.