A Multi-scale and Multi-pose Face Detection System

• Published in: Lecture notes in computer science pp. 268 - 276
• Main Authors: Nam, Mi-Young, Rhee, Phill-Kyu
• Format: Book Chapter Conference Proceeding
• Language: English
• Published: Berlin, Heidelberg Springer Berlin Heidelberg 2005; Springer
• Series: Lecture Notes in Computer Science
• Subjects: Active Shape Model; Applied sciences; Computer science; control theory; systems; Data processing. List processing. Character string processing; Exact sciences and technology; Face Detection; Face Image; Fuzzy ARTMAP; Mahalanobis Distance; Memory organisation. Data processing; Software; Computer vision; Face recognition; Video signal; Pattern recognition; Data mining; Real time; Modeling; Radial basis function; User interface; Multiscale method; Facies; Object oriented; Probability learning; Localization; Learning algorithm
• ISBN: 9783540288336; 3540288333; 3540287574; 9783540287575
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/11552499_30

In this paper, the framework and implementation of a real time multi-scale face detection system using appearance-based learning method and multi-pose hybrid learning approach. Multiple scale and pose based object detection is attractive since it could accumulate the face models by autonomous learning process. Face image, however, can be approximated even though it is represented with many scales. A real time face detection determines the location and size of each human face(if any) in an input image. Detecting varying human face in video frames is an important task in many computer vision applications such as human-computer interface. The face detection proposed in this paper employs hybrid learning approach and statistical method. We employ FuzzyART and RBF Network and Mahalanobis distance. We achieve a very encouraging experimental results.