Scale invariant face detection method using higher-order local autocorrelation features extracted from log-polar image

Abstract

This paper proposes a scale invariant face detection method which combines higher-order local autocorrelation (HLAC) features extracted from a log-polar transformed image with linear discriminant analysis for "face" and "not face" classification. Since HLAC features of log-polar images are sensitive to shifts of a face, we utilize this property and develop a face detection method. HLAC features extracted from a log-polar image become scale and rotation invariant because scalings and rotations of a face are expressed as shifts in a log-polar image (coordinate). By combining these features with the linear discriminant analysis which is extended to treat "face" and "not face" classes, a scale invariant face detection system can be realized.