DocumentCode :
2974618
Title :
A novel clustering method for Chernoff faces based on V-system
Author :
Song, Ruixia ; Zhao, Zhaoxia ; Ou, Meifang
Author_Institution :
Coll. of Sci., North China Univ. of Technol., Beijing, China
fYear :
2009
fDate :
22-24 June 2009
Firstpage :
1556
Lastpage :
1561
Abstract :
The Chernoff faces is a classical method to display multidimensional data graphically in Multivariate Statistics. Based on the V-system, a class of complete orthogonal function system on L2[0,1], a new method to quantify the overall features of Chernoff faces is proposed in this paper. Chernoff faces are firstly transformed into the frequency domain by the V-system, the overall features of Chernoff faces are then obtained. It offers a new programmed clustering method for Chernoff faces. Using it, self-adaptive clustering can carry out by computer. This self-adaptive clustering technique can avoid misjudgment caused by human eyes. Especially, when the number of data sets processing is very large, its advantage is more obvious. The results of the concrete experimental tests indicate that the novel method for clustering Chernoff faces is simple, fast and effective.
Keywords :
face recognition; pattern clustering; statistics; Chernoff faces; V-system; complete orthogonal function system; multidimensional data; multivariate statistics; programmed clustering method; self-adaptive clustering; Clustering methods; Eyes; Face detection; Facial features; Humans; Multidimensional systems; Solid modeling; Statistical analysis; Statistics; Visualization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information and Automation, 2009. ICIA '09. International Conference on
Conference_Location :
Zhuhai, Macau
Print_ISBN :
978-1-4244-3607-1
Electronic_ISBN :
978-1-4244-3608-8
Type :
conf
DOI :
10.1109/ICINFA.2009.5205165
Filename :
5205165
Link To Document :
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