On-line boosted cascade for object detection

On-line boosting is a recent advancement in the field of machine learning that has opened a new spectrum of possibilities in many diverse fields. With respect to a static strong classifier, the on-line algorithm updates the ensemble using new incoming samples. This idea has been successfully exploited in tasks such as detection and tracking as a classification problem with good results. Our purpose is to provide an efficient and robust framework to build a cascade of on-line updated classifiers that, speeding up the application time, allows the employment of a higher number of features, thus achieving better detection performance.

• Type: Conference
• Year: 2008
• Where: ICPR
• Authors: Ingrid Visentini, Lauro Snidaro, Gian Luca Foresti
• Keywords: Computer Vision, ICPR 2008, On-line Boosting, On-line Updated Classifiers, Static Strong Classifier