From Illustrations to sports videos: How can we utilize the data?

Pinar Duygulu
(Hacettepe University, Turkey)


In this talk, first I will present our recent efforts on leveraging large amounts images and videos on the web to design methods that learn from weakly labeled data. I will describe two methods for organization and cleaning of the data collected through text based querying and discuss the results on sport videos. With the focus on soccer videos, I will also show the results of another study on tracking players. In the second part, I will introduce a dataset collected from illustrations in children’s books and discuss about our initial findings.

Short Bio:

Pinar Duygulu has received her BSc, MSc and PhD degrees from Department of Computer Engineering at Middle East Technical University, Ankara, Turkey in 1996, 1998 and 2003 respectively. During her PhD, she was a visiting scholar at University of California at Berkeley under the supervision of Prof. David Forsyth. After being a post-doctoral researcher at Informadia Project at Carnegie Mellon University, she joined to Department of Computer Engineering at Bilkent University, Ankara, Turkey in 2004. During 2014 and 2015 she was at Carnegie Mellon University as a research associate. Currently, she is a faculty member at Department of Computer Engineering at Hacettepe University, Ankara, Turkey. She received Science Academy's Young Scientist Award (BAGEP) in 2015, Fulbright scholarship in 2013, TUBITAK Career award in 2005, and the best paper in Cognitive Vision award at European Conference on Computer Vision in 2002. Her current research interests include computer vision and multimedia data mining, specifically object, face and action recognition in large image and video collections and analysis of historical documents