Adam Schmidt

The Architecture and Performance of the Face and Eyes Detection System Based on the Haar Cascade Classifiers

Andrzej Kasiński, Adam Schmidt

In: Pattern Analysis & Applications

Vol.: 13

Nr: 2

Year: 2010

Pages: 197--211

Publisher's page:


The precise face and eyes detection is essential in many Human-Machine Interface systems. Therefore, it is necessary to develop a reliable and efficient object detection method. In this paper we present the architecture of a hierarchical face and eyes detection system using the Haar Cascade Classifiers (HCC) augmented with some simple knowledge based rules. The influence of the training procedure on the performance of the particular HCCs has been investigated. Additionally, we compared the efficiency of other authors' face and eyes HCCs with the efficiency of those trained by us. By applying the proposed system to the set of 10000 test images we were able to properly detect and precisely localize 94% of the eyes.