Real-Time Face Detection and Tracking Using PCA and NN

This paper proposes a real-time face detection and tracking method using principal component analysis (PCA) and neural network (NN). To improve the accuracy of the face detection, multiple methods are combined. For tracking a face, the PCA technique is used. The analysis of a set of images captured during the experiment revealed that the correct rate of face verification was an average 94.5%.

Authors and Affiliations

1. Dept. of computer engineering, Kyungpook National University, 702-701, 1370, Sangyuk-dong, Buk-gu, Daegu, Korea

   Chang-Woo Lee, Yeon-Chul Lee & Hang-Joon Kim

2. LG Electronics Inc., 730-702, 229, Gongdan-dong, Gumi, Korea

   Sang-Yong Bak

Editors and Affiliations

1. School of Information Science and Technology Department of Information and Communication Engineering, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656, Japan

   Mitsuru Ishizuka

2. School of Information Technology Knowledge Representation and Reasoning Unit (KRRU) Faculty of Engineering and Information Technology, Griffith University, PMB 50 Gold Coast Mail Centre, Queensland, 9726, Australia

   Abdul Sattar

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