Pose estimation using cascade trees

In this thesis, I implemented and extended a face detector, based on cascades of boosted features, for use in real time systems. The extensions are twofold. First, I designed a way of combining several cascades into a cascade tree, and showed how such a tree provides a powerful mechanism for combining detector efficiency and accuracy. When the training data has large variations, the cascade tree yields a faster detector, and when the data has only small variations, there is a distinct detection rate improvement. As a second extension, I designed a system for pose estimation based on an array of cascades. I performed an evaluation of this system and compared to normalized cross-correlation.

Department dc:contributor.department

Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2004

Author dc:creator

• Sundberg, Patrik P. (Patrik Per), 1980-

Advisor dc:contributor.advisor

• Trevor Darrell.

• Electrical Engineering and Computer Science.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/17985

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/17985