Title :
Package Boosting for Readaption of Cascaded Classifiers
Author :
Szczot, Magdalena ; Forster, Julian ; Löhlein, Otto ; Palm, Günther
Author_Institution :
Dept. Environ. Perception (GR/PAP), Daimler AG, Ulm, Germany
Abstract :
This contribution presents an efficient and useful way to readapt a cascaded classifier. We introduce Package Boosting which combines the advantages of Real Adaboost and Online Boosting for the realization of the strong learners in each cascade layer. We also examine the conditions which need to be fulfilled by a cascade in order to meet the requirements of an online algorithm and present the evaluation results of the system.
Keywords :
learning (artificial intelligence); pattern classification; cascaded classifiers; online boosting; package boosting; real Adaboost; Approximation algorithms; Boosting; Classification algorithms; Detectors; Equations; Estimation; Training; Classifier Readaption; Online Boosting;
Conference_Titel :
Pattern Recognition (ICPR), 2010 20th International Conference on
Conference_Location :
Istanbul
Print_ISBN :
978-1-4244-7542-1
DOI :
10.1109/ICPR.2010.140
