Hand Gesture Recognition and Face Detection in Images
Yang, Ming-Hsuan
This item is only available for download by members of the University of Illinois community. Students, faculty, and staff at the U of I may log in with your NetID and password to view the item. If you are trying to access an Illinois-restricted dissertation or thesis, you can request a copy through your library's Inter-Library Loan office or purchase a copy directly from ProQuest.
Permalink
https://hdl.handle.net/2142/81982
Description
Title
Hand Gesture Recognition and Face Detection in Images
Author(s)
Yang, Ming-Hsuan
Issue Date
2000
Doctoral Committee Chair(s)
Ahuja, Narendra
Department of Study
Computer Science
Discipline
Computer Science
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Computer Science
Language
eng
Abstract
Recently, Support Vector Machines (SVMs) have shown great potential in visual learning and pattern recognition problems. However, training a SVM for a large-scale problem is challenging since it is computationally intensive and the memory requirement grows with square of the number of training vectors. In the fourth part of this thesis, we have developed a geometric approach to train SVMs and compared its performance against conventional methods.
Use this login method if you
don't
have an
@illinois.edu
email address.
(Oops, I do have one)
IDEALS migrated to a new platform on June 23, 2022. If you created
your account prior to this date, you will have to reset your password
using the forgot-password link below.