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Faces: Art, And Computerized Evaluation Systems-A Feasibility Study Of The Application Of Face Recognition Technology To Works Of Portrait Art

技術優勢: Unmet curatorial and preservation need – help provide answers to art historians Identify artists’ styles and artists in order to attribute unknown work

技術應用: Help art historians verify authenticity and identification of the portrait’s artist and sitter System for identifying forensic & composite sketches to help law enforcement Potentially help identify handwriting & paleography (ancient writing)

*Abstract: Background:

Portraits are not just forms of art; they usually identify important people and the artistic styles of that era. Currently, face recognition technologies for portraits do not exist and therefore, many great pieces in museums remain unidentified. Curators spend an excruciating amount of time, energy and already limited resources to identify paintings. A computer program that helps answer these questions will be beneficial not only for art identification-sakes but to discover the historical stories behind unknown paintings.

Brief Description:

UCR researchers have developed a novel computerized system for identifying artists and artists’ styles. First, they fed known portraits into their algorithm for face recognition system training. Then, the Portrait Feature Space (PFS) feature analyzes the unknown portrait and looks for a match in the system. The system is able to learn artistic conventions, such as variation in brush strokes and facial proportion metrics, to compute a similarity score. Identity verification is a 2-step process where style modeling results in assigning the unknown portrait to a particular artist, then further authentication through analysis with known sitters.

*Applications

Help art historians verify authenticity and identification of the portrait’s artist and sitter
System for identifying forensic & composite sketches to help law enforcement
Potentially help identify handwriting & paleography (ancient writing)

*Principal Investigation: Name: Conrad Rudolph
Department:

Name: Amit Roy-Chowdhury
Department:

Name: Ramya Srinivasan
Department:

其他: Images

Wikimedia Commons / https://commons.wikimedia.org/wiki/File:Darnley_stage_3.jpg

Tech ID/UC Case
25255/2015-443-1

Related Cases
2015-443-1

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