Boosting-Based Face Detection and Adaptation

Cha Zhang; Zhengyou Zhang

ISBN 10: 160845133X / ISBN 13: 9781608451333

Editore: Morgan & Claypool, 2010

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Ex-library with the usual features. Library label on front cover. The interior is clean and tight. Binding is good. Cover shows light wear. Codice articolo 122154x

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Titolo: Boosting-Based Face Detection and Adaptation

Casa editrice: Morgan & Claypool

Data di pubblicazione: 2010

Legatura: Soft Cover

Condizione: Good

Tipologia articolo: Ex-Library

Descrizione articolo

Riassunto:

Face detection, because of its vast array of applications, is one of the most active research areas in computer vision. In this book, we review various approaches to face detection developed in the past decade, with more emphasis on boosting-based learning algorithms. We then present a series of algorithms that are empowered by the statistical view of boosting and the concept of multiple instance learning. We start by describing a boosting learning framework that is capable to handle billions of training examples. It differs from traditional bootstrapping schemes in that no intermediate thresholds need to be set during training, yet the total number of negative examples used for feature selection remains constant and focused (on the poor performing ones). A multiple instance pruning scheme is then adopted to set the intermediate thresholds after boosting learning. This algorithm generates detectors that are both fast and accurate. Table of Contents: A Brief Survey of the Face Detection Literature / Cascade-based Real-Time Face Detection / Multiple Instance Learning for Face Detection / Detector Adaptation / Other Applications / Conclusions and Future Work