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 tech-nique 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 ap-proach 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 per-formance. 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.