DocumentCode :
1783710
Title :
Category-Separating Strategy for branded handbag recognition
Author :
Yan Wang ; Sheng Li ; Kot, Alex C.
Author_Institution :
Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore, Singapore
fYear :
2014
fDate :
21-23 May 2014
Firstpage :
61
Lastpage :
64
Abstract :
In recent years, computer vision community has devoted efforts on the recognition of basic-level categories. On the other hand, finegrained object recognition which targets at recognizing objects belonging to the same basic-level class, is a more challenging problem and receives an increasing attention during recent years. In this paper, we propose a hierarchical structure Category-Separating Strategy for branded handbag recognition which is the first attempt to address the fine-grained object recognition on branded handbags. Experimental results on a newly constructed dataset are provided to show the effectiveness of the proposed methodology.
Keywords :
computer vision; object recognition; basic-level categories; branded handbag recognition; category-separating strategy; computer vision community; fine-grained object recognition; Accuracy; Computer vision; Conferences; Feature extraction; Image color analysis; Pattern recognition; Visualization; fine-grained; handbag dataset; object recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communications, Control and Signal Processing (ISCCSP), 2014 6th International Symposium on
Conference_Location :
Athens
Type :
conf
DOI :
10.1109/ISCCSP.2014.6877816
Filename :
6877816
Link To Document :
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