This paper proposes a Network Shaped Cascade Classifier(NSCC) based on potential functions for pedestrian detection. Potential function is exploited to capture the nonlinear information in the training set based on the multiple sample centers. A flexible structure in NSCC is used to combine the base classifier and potential function into a nonlinear cascade classifier, and NSCC can well inherit the advantages of the base classifier. We test our classifier on INRIA dataset, and achieve a much better performance than support vector machine.
A network shaped cascade classifier based on potential functions for pedestrian detection
2014-08-01
231380 byte
Conference paper
Electronic Resource
English
A Cascaded Classifier for Pedestrian Detection
IEEE | 2006
|A Cascaded Classifier for Pedestrian Detection
British Library Conference Proceedings | 2006
|On Exploration of Classifier Ensemble Synergism in Pedestrian Detection
Online Contents | 2010
|