Face detection by discrete Gabor jets and reference graph of fiducial points

Authors:
Jacek Naruniec;Władysław Skarbek
Affiliations:
Warsaw University of Technology, Faculty of Electronics and Information Technology, Warszawa, Poland;Warsaw University of Technology, Faculty of Electronics and Information Technology, Warszawa, Poland
Venue:
RSKT'07 Proceedings of the 2nd international conference on Rough sets and knowledge technology
Year:
2007

Citing 3
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Introduction to statistical pattern recognition (2nd ed.)

Introduction to statistical pattern recognition (2nd ed.)
A decision-theoretic generalization of on-line learning and an application to boosting

Journal of Computer and System Sciences - Special issue: 26th annual ACM symposium on the theory of computing & STOC'94, May 23–25, 1994, and second annual Europe an conference on computational learning theory (EuroCOLT'95), March 13–15, 1995
Detecting Faces in Images: A Survey

IEEE Transactions on Pattern Analysis and Machine Intelligence

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Abstract

A novel face detection scheme is described. The facial feature extraction algorithm is based on discrete approximation of Gabor Transform, called Discrete Gabor Jets (DGJ), evaluated in fiducial face points. DGJ is computed using integral image for fast summations in arbitrary windows, and by FFT operations on short contrast signals. Contrasting is performed along radial directions while frequency analysis along angular direction. Fourier coefficients for a small number rings create a long vector which is next reduced to few LDA components. Four fiducial points are only considered: two eye corners and two nose corners. Fiducial points detection is based on face/nonface classifier using distance to point dependent LDA center and threshold corresponding to equal error rate on ROC. Finally, the reference graph is used to detect the whole face. The proposed method is compared with the popular AdaBoost technique and its advantages and disadvantages are discussed.