DocumentCode :
3253058
Title :
Genetic programming based classifier in Viola-Jones RapidMiner Image Mining Extension
Author :
Karasek, Jan ; Burget, Radim ; Masek, Jaroslav ; Benda, Ondrej
Author_Institution :
Dept. of Telecommun., Brno Univ. of Technol., Brno, Czech Republic
fYear :
2013
fDate :
2-4 July 2013
Firstpage :
872
Lastpage :
876
Abstract :
This paper presents a new approach to the classifier design used in the Viola-Jones object detector implemented in RadpidMiner Image Mining Extension. The new approach to the classifier design proposed in this paper is in fact creation of a classification tree designed by a genetic programming algorithm. The resulting classifier is used as an alternative approach to the standard cascade classifier designed by a genetic algorithm. In this paper, a classifier design is shown, the incorporation into the Viola-Jones operator is described, and experimental results of face classification process are depicted and compared to the standard cascade classifier designed by genetic algorithm.
Keywords :
data mining; face recognition; genetic algorithms; image classification; Viola-Jones RapidMiner Image Mining Extension; Viola-Jones object detector; cascade classifier design; classification tree; face classification process; genetic programming based classifier; Accuracy; Algorithm design and analysis; Face; Feature extraction; Genetic programming; Sociology; Statistics; Classification Tree; Genetic Programming; Image Mining Extension; Object Classification; RapidMiner;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Telecommunications and Signal Processing (TSP), 2013 36th International Conference on
Conference_Location :
Rome
Print_ISBN :
978-1-4799-0402-0
Type :
conf
DOI :
10.1109/TSP.2013.6614064
Filename :
6614064
Link To Document :
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