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Abstract: This project is based on two face detection algorithms developed by Paul Viola and Michael Jones [6],[7]. Using a training set of positive and negative images (where the positive instances contain human faces), the algorithms use AdaBoost [3] to build a robust scale-invariant image classifier for face detection. My motivation for exploring the Viola and Jones face detection framework is to gain experience with boosting and to explore issues and obstacles concerning the application of machine... (Update)
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BibTeX entry: (Update)
P. S. Carbonetto. "Robust Object Detection Using Boosted Learning." Department of Computer Science, University of British Columbia, Vancouver, April 2002. http://citeseer.ist.psu.edu/carbonetto02robust.html More
@misc{ carbonetto02robust,
author = "P. Carbonetto",
title = "Robust Object Detection Using Boosted Learning",
text = "P. S. Carbonetto. Robust Object Detection Using Boosted Learning. Department
of Computer Science, University of British Columbia, Vancouver, April 2002.",
year = "2002",
url = "citeseer.ist.psu.edu/carbonetto02robust.html" }
Citations (may not include all citations):145 Rapid object detection using a boosted cascade of simple fea.. - Viola, Jones - 2001
104 Robust real-time object detection - Viola, Jones - 2001
68 Pedestrian detection using wavelet templates - Oren, Papageorgiou et al. - 1997
33 The Boosting approach to machine learning: an overview - Schapire - 2002
4 A General Framework for Object Detection (context) - Papageorgiou, Oren et al. - 1998
2 Wavelets for computer graphics: a primer part - Stollnitz, DeRose et al. - 1995
1 Boosting sparse representations for image retrieval (context) - Tieu - 2000
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