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In order to enhance the ensemble of the traditional Adaboost algorithm and reduce its complexity, two improved Adaboost algorithms are proposed, which are based on the correlation of classifiers. In the algorithm, Q-statistic is added in the training weak classifiers, every weak classifier is related not only to the current classifier, but also to previous classifiers as well, which can effectively...
Face detection is a widely studied topic in computer vision. Despite of its great success, several key problems are still unresolved for AdaBoost algorithms: how to select the asymmetric weak learners and how to combine added sample sets.In this paper,a new combined asymmetric AdaBoost algotithms is proposed to make improvement in the two aspects.First we select the asymmetric weak learners by computering...
To overcome feature redundancy in the construction of human face detector with AdaBoost algorithm, an improved human face detection method is proposed. First, eight new rectangle feature types are proposed and AdaBoost algorithm is used as a feature selector to make rough selections. Then genetic algorithm with strong search ability is introduced to optimize those selected features and their parameters...
This article describes functions and advantages of the OpenCV library, and explains the meaning, development status, applications, and difficulties of face detection technology, analysis the idea of Adaboost classifier algorithm, and achieves the detection procedures for face using OpenCV, and proposes the improved method based on the the original algorithm.
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