Face Recognition Using ALLE and SIFT for Human Robot Interaction

Authors:
Yaozhang Pan;Shuzhi Sam Ge;Hongsheng He
Affiliations:
Social Robotics Lab, Interactive and Digital Medial Institute, Department of Electrical and Computer Engineering, National University of Singapore 117576;Social Robotics Lab, Interactive and Digital Medial Institute, Department of Electrical and Computer Engineering, National University of Singapore 117576;Social Robotics Lab, Interactive and Digital Medial Institute, Department of Electrical and Computer Engineering, National University of Singapore 117576
Venue:
Proceedings of the FIRA RoboWorld Congress 2009 on Advances in Robotics
Year:
2009

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Abstract

Face recognition is a very important aspect in developing human-robot interaction (HRI) for social robots. In this paper, an efficient face recognition algorithm is introduced for building intelligent robot vision system to recognize human faces. Dimension deduction algorithms locally linear embedding (LLE) and adaptive locally linear embedding (ALLE) and feature extraction algorithm scale-invariant feature transform (SIFT) are combined to form new methods called LLE-SIFT and ALLE-SIFT for finding compact and distinctive descriptors for face images. The new feature descriptors are demonstrated to have better performance in face recognition applications than standard SIFT descriptors, which shows that the proposed method is promising for developing robot vision system of face recognition.