The Classification of Style in Fine-Art Painting
Summary
The computer science approaches to the classification of painting concentrate on problems of attribution. While this goal is certainly worthy of pursuit, there are other valid tasks related to the classification of painting including the identification of period styles, the description of styles, and the analysis of the relationship between diferent painting styles. This dissertation proposed and developed a general approach to the classification of style and achieved this goal using a semantically-relevant feature set. The resulting automated painting analysis system supports the following tasks: recognize painting styles, identify key relationships between styles, outline the basis for style proximity, and evaluate and visualize classification results.
Dissertation
Details
- Dissertation Advisors: Dr. Charles Tappert, Dr. Sung-Hyuk Cha
- Committee Members: Dr. Fred Grossman, Dr. Michael Gargano
- Defense Date: 05/13/2005
- Final Draft Submitted: 08/23/2005
Education
Education Summary
Pace University, D.P.S.
August, 2002 to September, 2005
Pace University, M.S.
June, 1997 to June, 1999
Fordham University, M.A.
September, 1995 to February, 1997
SUNY Geneseo, B.A.
September, 1990 to June, 1994
June, 1997 to June, 1999
September, 1995 to February, 1997
September, 1990 to June, 1994
Pace University
For more than 100 years, Pace University has been preparing students to become leaders in their fields by providing an education that combines exceptional academics with professional experience and the New York advantage. Pace has three campuses, in New York City, Westchester, and White Plains. A private metropolitan university, Pace enrolls approximately 13,500 students in bachelor's, master's, and doctoral programs in the Dyson College of Arts and Sciences, Lienhard School of Nursing, Lubin School of Business, School of Education, Seidenberg School of Computer Science and Information Systems, and School of Law.