Method for combining boosted classifiers for efficient multi-class object detection

A computer implemented method for training a system for detecting multi-class objects in an image or a video sequence, the method performed by the computer comprising the steps of:

• identifying an ensemble of weak binary classifiers that are common to a set of object classes, wherein each object class shares a common set of features with the other object classes, and wherein each feature of said common set of features is associated with a weak binary classifier in said ensemble of weak binary classifiers,
• for each object class, forming an individual strong classifier by adapting a separate set of weights for the ensemble of weak classifiers, wherein a same ensemble of weak binary classifiers is incorporated into each individual strong classifier by the separate set of weights for each object class,
• wherein said steps of identifying an ensemble of weak binary classifiers and, for each object class, forming an individual strong classifier are performed by a computer processor.