Artibus et Historiae no. 75 (XXXVIII)
2017, ISSN 0391-9064Up
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CONRAD RUDOLPH, AMIT ROY-CHOWDHURY, RAMYA SRINIVASAN, AND JEANETTE KOHL - FACES: Faces, Art, and Computerized Evaluation Systems – A Feasibility Study of the Application of Face Recognition Technology to Works of Portrait Art (pp. 265–291)
FACES (Faces, Art, and Computerized Evaluation Systems) is a project that, after two years of research support from the National Endowment for the Humanities (NEH), has established proof of concept for the application of face recognition technology to works of portrait art. In the application of face recognition technology to photographed human faces, a number of difficulties are inherent in a real or perceived alteration of appearance of the face through variations in facial expression, age, angle of pose, and so on. With works of portrait art, not only do all these problems pertain, but these works also have their own additional challenges. Most notably, portrait art does not provide what might be called a photographic likeness but rather one that goes through a process of visual interpretation on the part of the artist. After establishing the initial parameters of the application of this technology, the main goal of FACES has been to test the ability of the FACES algorithm to restore lost identities to works of portrait art, something our research has shown is clearly feasible. Our work has also suggested a number of other potential applications, both using the FACES algorithm and employing basic concept of FACES in an altered form.
The use of the FACES algorithm should not be thought of as limited to facial recognition in the sense of identification alone. An altered form of the technology used in FACES might also be used to study a wide range of other applications such as adherence or non-adherence to widely recognized artistic canons, formal or informal; the identification of variations in the practice of an individual artist (over time, with different subjects, with different genres, after exposure to external influences, and so on); probable bodies of work of anonymous artists; difference in larger bodies of works (art historical ‘big data’); even to detect the change of masons in medieval building.