Babak Saleh, Ph.D. candidate, Department of Computer Science Rutgers University
Artistic AI: Analyzing Visual Culture Through the Eyes of a Machine
12:30 – 1:30 PM
Tuesday, September 20, 2016
Education 115
Abstract: In the past few years, collections of digitized fine-art paintings have been expanded rapidly, both in the size and variety of artworks. This brings up an extensive list of traditional challenges from data storage to visual classification. Additionally the opportunity of having access to large-scale collection of artworks opens the door for novel knowledge discovery research problems. My colleagues and I at the Art and AI lab at Rutgers University have been working on all the aforementioned tasks.
In this talk, I will first cover our published results on the well-known task of painting tagging based on Style, Genre, and Artists. I will explain the applicability of visual features for the analysis of paintings, and how we tuned them to work on a large-collection of paintings.
Next, I will explain our proposed algorithms for finding influence paths between artists based on their artworks based on visual analysis of the content of the images. Additionally, I will elaborate how we built a large network of paintings and quantified the creativity of these artworks based on their novelty and influence. Finally, I will show results of validating our computational models on modern art data where we show that the model coincides with the aggregate of the opinions of art historian experts.
Speaker Bio: Babak Saleh is a Ph.D. candidate in the department of computer science at Rutgers University, where he conducts research in the intersection of computer vision, machine learning, and human perception. Inspired by human visual perception, he has developed computational models for measuring typicality of an image and its application in learning more robust visual classifiers. He holds an MS in Computer Science and a second MS in Statistics from Rutgers University. He completed his undergraduate studies in Computer Science and Mathematics at the Sharif University of Technology in Tehran, Iran. He is the recipient of outstanding student paper award from AAAI 2016, and NSF I-Corps award. His research has been recognized by major media and press outlets, including NBC News, PBS, New York Times, Washington Post, WIRED, Fast Company and IEEE MultiMedia.