A Model Based Framework for Object Detection via Data Transformation - Tapa blanda

Guo, Peifang; Bhattacharya, Prabir

 
9783659494574: A Model Based Framework for Object Detection via Data Transformation
Tapa blanda
ISBN 10: 3659494577 ISBN 13: 9783659494574
Editorial: LAP LAMBERT Academic Publishing, 2013

Sinopsis

The dynamic synthesis of nonlinear feature functions is a challenging problem in object detection. This book presents a combinatorial approach of genetic programming and the expectation maximization algorithm (GP-EM) to synthesize nonlinear feature functions automatically for the purpose of object detection. The EM algorithm investigates the use of Gaussian mixture which is able to model the behaviour of the training samples during an optimal GP search strategy. Based on the Gaussian probability assumption, the GP-EM method is capable of performing simultaneously dynamic feature synthesis and model-based generalization. The EM part of the approach leads to the application of the maximum likelihood (ML) operation which provides protection against inter-cluster data separation and thus exhibits improved convergence. The experimental results show that the approach improves the detection accuracy and efficiency of pattern object discovery, as compared to some state-of-the-art methods for object detection existing in the literature.

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Reseña del editor

The dynamic synthesis of nonlinear feature functions is a challenging problem in object detection. This book presents a combinatorial approach of genetic programming and the expectation maximization algorithm (GP-EM) to synthesize nonlinear feature functions automatically for the purpose of object detection. The EM algorithm investigates the use of Gaussian mixture which is able to model the behaviour of the training samples during an optimal GP search strategy. Based on the Gaussian probability assumption, the GP-EM method is capable of performing simultaneously dynamic feature synthesis and model-based generalization. The EM part of the approach leads to the application of the maximum likelihood (ML) operation which provides protection against inter-cluster data separation and thus exhibits improved convergence. The experimental results show that the approach improves the detection accuracy and efficiency of pattern object discovery, as compared to some state-of-the-art methods for object detection existing in the literature.

Biografía del autor

Peifang Guo:Postdoctoral researcher at University of Cincinnati in USA; Prabir Bhattacharya: Professor at University of Cincinnati in USA.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
LAP LAMBERT Academic Publishing
Año de publicación
2013
Idioma
Inglés
ISBN 10 
3659494577
ISBN 13 
9783659494574
Encuadernación
Tapa blanda
Número de páginas
64
Contacto del fabricante
no disponible
Persona responsable
no disponible