Multiclass Adaboost and Coupled Classifiers for Object Detection

Building robust and fast multiclass object detection systems is a important goal of computer vision. In the present paper we extend the well-known work of Viola and Jones on boosted cascade classifiers to the multiclass case with the goal of building multiclass and multiview object detectors. We propose to use nested cascades of multiclass boosted classifiers and we introduce the concept of coupled components in multiclass classifiers. We evaluate the system by building several multiview face detectors, each one built to detect a different number of classes. Thus, we present results showing how well the system scales. Promising results are obtained in the BioID database, showing the potentiality of the proposed methods for building object detectors.