Scale Invariant Face Detection and Classification Method Using Shift Invariant Features Extracted from Log-Polar Image (Special Issue on Biometric Person Authentication)

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copyright(c)2001 IEICE許諾番号：07RB0174　http://www.ieice.org/jpn/trans_online/index.htmlThis paper presents a scale invariant face detection and classification method which uses shift invariant features extracted from a Log-Polar image. Scale changes of a face in an image are represented as shift along the horizontal axis in the Log-Polar image. In order to obtain scale invariant features, shift invariant features are extracted from each row of the Log-Polar image. Autocorrelations, Fourier spectrum, and PARCOR coefficients are used as shift invariant features. These features are then combined with simple classification methods based on Linear Discriminant Analysis to realize scale invariant face detection and classification. The effectiveness of the proposed face detection method is confirmed by experiments using face images captured under different scales, backgrounds, illuminations, and dates. To evaluate the proposed face classification method, we performed experiments using 2,800 face images with 7 scales under 2 different backgrounds and face images of 52 persons.
社団法人電子情報通信学会の論文
2001-07-01