DocumentCode :
1710446
Title :
Adaptive Weighted Multi-Element Collaborative Representation for Visual Classification
Author :
GangLong Duan ; Long Wei ; Jianren Wang ; Hongqi Wang
Author_Institution :
Dept. of Manage. Sci. & Eng., Xi´an Univ. of Technol., Xi´an, China
fYear :
2013
Firstpage :
1
Lastpage :
5
Abstract :
Adaptive Weighted Multi-Element Collaborative Representation for Visual Classification is proposed in this paper. To address the weak discriminative power of SRC (sparse representation classifier) method, we propose using multiple elements to represent each element and construct multiple collaborative representation for classification. To reflect the different element with different importance and discriminative power, we present an adaptive weighted residuals method to linearly combine different element representations for classification. Experimental results demonstrate the effectiveness and better classification accuracy of our proposed method.
Keywords :
image classification; image representation; SRC method; adaptive weighted multielement collaborative representation; adaptive weighted residuals method; sparse representation classifier method; visual classification; weak discriminative power; Classification algorithms; Collaboration; Databases; Face; Face recognition; Testing; Training; Collaborative representation; SRC; adaptive weighted residuals;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information, Communications and Signal Processing (ICICS) 2013 9th International Conference on
Conference_Location :
Tainan
Print_ISBN :
978-1-4799-0433-4
Type :
conf
DOI :
10.1109/ICICS.2013.6782782
Filename :
6782782
Link To Document :
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