A Model Based Framework for Object Detection via Data Transformation

Language: English

Published by LAP LAMBERT Academic Publishing Dez 2013, 2013

3659494577 / 9783659494574

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This item is printed on demand - Print on Demand Titel. Neuware -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.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 64 pp. Englisch.

Seller Inventory # 9783659494574

Title
A Model Based Framework for Object Detection via Data Transformation
Author
Peifang Guo
Publisher
LAP LAMBERT Academic Publishing Dez 2013
Publication year
2013
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
3659494577
ISBN 13
9783659494574
Item weight
113 grams
Dimensions
220x150x5 mm

buchversandmimpf2000

Emtmannsberg, BAYE, Germany

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