Hand Gesture Recognition and Face Detection in Images

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.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Computer Science

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2015

Author dc:creator

• Yang, Ming-Hsuan

Contributors dc:contributor

• Ahuja, Narendra

• Computer Science

Language dc:language

eng

Identifier

(MiAaPQ)AAI9971227

OAI record oai:identifier

https://www.ideals.illinois.edu/oai-pmh?verb=GetRecord&metadataPrefix=etdms&identifier=oai%3Awww.ideals.illinois.edu%3A2142%2F81982