http://www.cnr.it/ontology/cnr/individuo/prodotto/ID95121

Object detection in images: complexity reduction and parameter selection (Contributo in atti di convegno)

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Object detection in images: complexity reduction and parameter selection (Contributo in atti di convegno) (literal)

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Ancona N. 1, Cicirelli G. 1, Stella E. 1, Distante A. 1 (2003)
Object detection in images: complexity reduction and parameter selection
in ANNIE, St. Louis, Missouri
(literal)

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The product is published in the Proc. of ANNIE 2002 which is organized by the University of Rolla, Smart Engineering Systems Laboratory. The focus of the conference is Smart Engineering Design: neural Networks, Fuzzy Logic, Evolutionary Programming, Complex Systems and Artificial Life. (literal)

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This paper focuses on two central issues regarding the application of Support Vector Machines (SVM) for classification in real contexts. The first one concerns the reduction of the computational complexity of a reference classifier during testing, without increasing its generalization error. At this aim we use Principal Component Analysis (PCA) and we explicitly map the new input space in the feature space induced by the adopted kernel function. The second issue concerns the problem of parameter selection. In particular we show that the Receiver Operating Characteristic (ROC) curves, measured on a suitable validation set, are effective for selecting, among the classifiers the machine implements, the one having performances similar to the reference classifier. We address these two issues in the context of object detection in images and in particular for the specific problem of detecting goal during a football match. (literal)

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