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Published in:
2010 | OriginalPaper | Chapter
Feature Type and Size Selection for AdaBoost Face Detection Algorithm
Author : Jerzy Dembski
Published in: Image Processing and Communications Challenges 2
Publisher: Springer Berlin Heidelberg
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The article presents different sets of Haar-like features defined for adaptive boosting (AdaBoost) algorithm for face detection. Apart from a simple set of pixel intensity differences between horizontally or vertically neighboring rectangles, the features based on rotated rectangles are considered. Additional parameter that limits the area on which the features are calculated is also introduced. The experiments carried out on the set of MIT 19×19 face and non-face examples showed the usefulness of particular types of features and their influence on generalization.