Adaptive face recognition for low-cost, embedded human-robot interaction

Abstract

This paper presents an accelerated AdaBoost face detection algorithm and an incremental PCA-based face recognition algorithm for human robot interactive applications. The accelerated AdaBoost algorithm utilizes an image resizing technique and a skin color filter for detecting face regions. To track a detected face precisely and efficiently while also recognizing the face, a hybrid face tracking approach is applied based on an adaptive skin color mode and an estimated potential face area. In addition, a novel adaptive face recognition method is implemented by automatically upgrading the set of sample faces of a known person and collecting new samples of an unknown person with incrementally enhanced recognition performance. These algorithms are well suited for embedded systems, such as socially interactive robots, because of their cost and time efficiency and little pre-training required for reliable performance. © 2013 Springer-Verlag.