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
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