Viola-Jones Based Detectors: How Much Affects the Training Set?

摘要

This paper presents a study on the facial feature detection performance achieved using the Viola-Jones framework. A set of classifiers using two different focuses to gather the training samples is created and tested on four different datasets covering a wide range of possibilities. The results achieved should serve researchers to choose the classifier that better fits their demands.