Abstract
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.
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Nam, MY., Rhee, PK. (2005). A Multi-scale and Multi-pose Face Detection System. In: Singh, S., Singh, M., Apte, C., Perner, P. (eds) Pattern Recognition and Image Analysis. ICAPR 2005. Lecture Notes in Computer Science, vol 3687. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11552499_30
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DOI: https://doi.org/10.1007/11552499_30
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28833-6
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